Source: https://ailoot.ai/models/en/gemini-2-5-pro/
Canonical: https://ailoot.ai/models/en/gemini-2-5-pro/
Language: en

# Google: Gemini 2.5 Pro

[Markdown](https://ailoot.ai/models/en/gemini-2-5-pro/index.md) · [JSON](https://ailoot.ai/models/en/gemini-2-5-pro/facts.json)

## [Google: Gemini 2.5 Pro](https://ailoot.ai/models/en/gemini-2-5-pro/)

Gemini 2.5 Pro is Google’s stable thinking model for complex code, mathematics, STEM and long-context analysis. It accepts text, images, audio, video and PDF and returns text, with tools and structured output. Its dynamic reasoning budget supports 128–32,768 tokens and cannot be fully disabled.

- [**Ailoot · Anthropic Messages** `POST /v1/messages` `gemini-2.5-pro`](https://ailoot.ai/models/en/gemini-2-5-pro/#method-0)
- [**Ailoot · Gemini generateContent** `POST /v1beta/models/{model}:generateContent` `gemini-2.5-pro`](https://ailoot.ai/models/en/gemini-2-5-pro/#method-1)
- [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `gemini-2.5-pro`](https://ailoot.ai/models/en/gemini-2-5-pro/#method-2)
- [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `gemini-2.5-pro`](https://ailoot.ai/models/en/gemini-2-5-pro/#method-3)
- [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `google/gemini-2.5-pro`](https://ailoot.ai/models/en/gemini-2-5-pro/#method-4)
- [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `google/gemini-2.5-pro`](https://ailoot.ai/models/en/gemini-2-5-pro/#method-5)

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

Gemini 2.5 Pro is Google’s stable thinking profile for advanced coding, mathematics, STEM and long-context analysis. It can comprehend text, audio, images, video and entire code repositories, and its Gemini API profile also accepts PDF input. The output is text, including code, written analysis or a structured record. A useful assignment provides the evidence and asks for a result that can be checked, such as an explained solution, a codebase finding or a comparison across several documents.

For coding, supply the relevant files, observed behaviour and the change or question that matters. Long context can help the model relate modules rather than reason from one isolated snippet. For a code-path investigation, ask it to trace an identifier from an input form through processing and storage, identify where a contract changes and propose a focused correction. Preserve constraints and ask for supporting references. A proposed revision needs comparison with the actual code and any validation performed through the connected tools.

For mathematics or scientific analysis, state the problem, assumptions, units and required form of the answer. Supply data or figures that the calculation depends on. Ask for the supported result and the checks that make it assessable, such as boundary cases or a comparison with the original values. The model’s reasoning capability does not remove ambiguity in the problem statement. Keep an unknown quantity or unsupported assumption visible rather than replacing it with a convenient value.

Dynamic thinking is the documented default. The Gemini 2.5 GenerateContent guide supports an explicit reasoning budget from 128 to 32,768 tokens for Pro, or -1 for adaptive thinking. This edition cannot fully disable thinking. Those controls differ from Flash’s zero-budget option and from Gemini 3 thinking-level settings. The thinking budget guides reasoning rather than guaranteeing an exact number of internal tokens, and a response cap also needs to leave space for the final artifact.

For multimodal document work, identify the pages, chart, image region or recording event that should support the answer. A practical synthesis task can request the competing claims from several source documents, their supporting passages and the differences that matter to one decision. Ask the model to distinguish a stated fact from an inference. For video or audio, define whether the result should be a description, transcript, summary or comparison. The image and sound are evidence for a text result in this profile.

The exact API page documents function calling, code execution, file search, search grounding, Maps grounding, URL context and structured outputs. Define function purposes and parameter fields and preserve the real results in later turns. For a schema-constrained record, specify required fields and how missing information should be represented. The native architecture is a multimodal sparse mixture-of-experts transformer; that model design does not itself supply an external tool execution or a finished application beyond the text or code returned.

The native card lists a 1M input context and 64K text output; the API table specifies 1,048,576 input tokens and 65,536 output tokens. Instructions, source content and retained history contribute to input preparation. A maximum response allowance includes reasoning tokens, so an overly small cap can interrupt the final answer. Caching and batch processing are documented, together with Flex and Priority options. Retain each source identifier and the requested final form when preparing independent long-context tasks.

The stable identifier is distinct from the Experimental and Preview editions discussed separately in the shared Pro model card. Do not assign their version-specific results to this profile merely because they share the Pro name. The card identifies possible hallucinations and limitations in causal understanding, complex deduction and counterfactual reasoning, with a January 2025 knowledge cutoff. Supply current evidence when it matters and review source references, calculations and proposed modifications. The useful output is the supported text or code artifact the task requested.

Practical task

### Trace an identifier through storage

Technical example in English

```
Trace an identifier through storage

Trace this identifier through three excerpts: form sends {customer_id:'0017'}; service computes id=Number(body.customer_id); repository stores String(id). Requirement: preserve leading zeros. Identify where the contract changes, propose a minimal consistent correction and give tests for '0017', '17' and a missing ID. Do not claim the tests were executed.
```

#### Expected result

```
A source-path explanation, a proposed patch and a three-case regression-test plan.
```

#### Check the result

```
Check that the proposed path preserves distinct strings 0017 and 17 while specifying missing-ID behavior.
```

**Ailoot · Anthropic Messages** `POST /v1/messages` `gemini-2.5-pro`

[`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=messages)

Google /`gemini-2.5-pro`

### Overview

Gemini 2.5 Pro is Google’s stable thinking model for complex code, mathematics, STEM and long-context analysis. It accepts text, images, audio, video and PDF and returns text, with tools and structured output. Its dynamic reasoning budget supports 128–32,768 tokens and cannot be fully disabled.

Accepted inputs

Text · Images

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot · Anthropic Messages** `POST /v1/messages`

Input types

`text`, `image`

Output types

`text`

Context

1,048,576 tokens

Maximum output

65,536 tokens

Output format

json or SSE

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits gemini-2.5-pro | Default— |
| Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— |
| Field`messages[].role` | Type`string` | RequirementRequired | Values & limits user, assistant | Default— |
| Field`messages[].content` | Type`string\|content_block[]` | RequirementRequired | Values & limits | Default— |
| Field`system` | Type`string\|content_block[]` | RequirementOptional | Values & limits | Default— |
| Field`max_tokens` | Type`integer` | RequirementRequired | Values & limits Minimum: 1 Limit applies to: exact selected model/card ceiling | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse |
| Field`temperature` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`top_p` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`stop_sequences` | Type`string[]` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`tools` | Type`tool[]` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`tools[].name` | Type`string` | RequirementOptional | Values & limits Applies when: tool supplied | Default— |
| Field`tools[].description` | Type`string` | RequirementOptional | Values & limits | Default— |
| Field`tools[].input_schema` | Type`JSON_schema` | RequirementOptional | Values & limits | Default— |
| Field`tool_choice` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`thinking.type` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`thinking.budget_tokens` | Type`integer` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`output_config.effort` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`metadata` | Type`object` | RequirementOptional | Values & limits | Default— |
| Field`cache_control` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— |

Input material combinations

**Text** · UTF8 text

`messages[].content or type=text block`

**Text + image**

`{type:image,source:{type:base64,media_type,data}} or source type=url`

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`material_types` | Contracttext, image |
| Parameter`required` | Contractmodel, messages, max\_tokens |
| Parameter`optional_controls` | Contractnull |
| Parameter`content_type` | Contractapplication/json |
| Parameter`text_file_material` | Contractactual UTF-8 content inserted as text; file IDs/URLs need separate exact support |

Lifecycle: `exact retained published method`

Method shapes and IDs are exact; supplier capability is separate from admission.

### Pricing

#### Ailoot method rates

Input

$0.00125 */ 1K*

Output

$0.01 */ 1K*

Cache read

$0.000125 */ 1K*

#### Prices by request length · Anthropic Messages

| Request size, tokens | Input | Output | Cache read | Cache write | 5 min cache | 1 hour cache |
| --- | --- | --- | --- | --- | --- | --- |
| Request size, tokens(0; 200,000\] | Input$0.00125 | Output$0.01 | Cache read$0.000125 | Cache writeBase: — | 5 min cacheBase: — | 1 hour cacheBase: — |
| Request size, tokens(200,000; ∞) | Input$0.0025 | Output$0.015 | Cache read$0.00025 | Cache writeBase: — | 5 min cacheBase: — | 1 hour cacheBase: — |

Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

#### Reference tariff details

Model-level reference schedules do not change method selection, quotes or charges. Active charges use the selected Ailoot method rates.

Model reference schedules

#### Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

| Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge |
| --- | --- | --- | --- | --- |
| ConfigurationOpenAI Chat · Base token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens Output · Reasoning output tokens **$0.02** / 1K tokens |
| ConfigurationOpenAI Chat · Request-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationOpenAI Chat · Request-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationAnthropic Messages · Base token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens Output · Reasoning output tokens **$0.02** / 1K tokens |
| ConfigurationAnthropic Messages · Request-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationAnthropic Messages · Request-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

### Example requests

#### Ailoot · Anthropic Messages

Text exampleImage inputPython SDKNode.js SDKPython stream

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"
export AILOOT_TEXT_FILE
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model": "gemini-2.5-pro", "max_tokens": 1024, "messages": []}')
f=Path(os.environ["AILOOT_TEXT_FILE"])
if not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")
text=f.read_text(encoding="utf-8")
if not text.strip():raise SystemExit("Source material must contain text")
p["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\n\n"+text}]
Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \
  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path
print(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))
PY_RESULT
```

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"
export AILOOT_IMAGE_FILE
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model": "gemini-2.5-pro", "max_tokens": 1024, "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')
import base64
f=Path(os.environ["AILOOT_IMAGE_FILE"])
if not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")
raw=f.read_bytes()
mime="image/png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "image/jpeg" if raw.startswith(b"\xff\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None
if not mime:raise SystemExit("Use PNG JPEG or WebP")
b64=base64.b64encode(raw).decode()
p["messages"][0]["content"].append({"type":"image","source":{"type":"base64","media_type":mime,"data":b64}})
Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \
  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path
print(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))
PY_RESULT
```

```python
import anthropic
import os

if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")
client = anthropic.Anthropic(base_url="https://api.ailoot.ai", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)
msg = client.messages.create(
    model="gemini-2.5-pro",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}],
)
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

save_result(msg.to_dict(mode="json"))
```

```js
import Anthropic from "@anthropic-ai/sdk";

if (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");
const client = new Anthropic({ baseURL: "https://api.ailoot.ai", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });
const msg = await client.messages.create({
  model: "gemini-2.5-pro",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }],
});
import { writeFileSync } from "node:fs";

function saveResult(data, stem = "result") {
  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));
  console.log(JSON.stringify(data, null, 2));
  const saveBlob = (encoded, suffix, label) => {
    const raw = Buffer.from(encoded, "base64");
    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;
    const file = `${stem}-${label}.${ext}`;
    writeFileSync(file, raw); console.log("Saved", file);
  };
  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));
  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));
  for (const [i, item] of (data.output || []).entries()) {
    console.log("Output", i, JSON.stringify(item));
    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);
  }
  for (const [ci, candidate] of (data.candidates || []).entries()) {
    for (const [pi, part] of (candidate.content?.parts || []).entries()) {
      console.log("Candidate/part", ci, pi, JSON.stringify(part));
      const blob = part.inlineData || part.inline_data;
      if (blob?.data) {
        const mime = blob.mimeType || blob.mime_type;
        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";
        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);
      }
    }
  }
}

saveResult(msg);
```

```python
import anthropic,os
from pathlib import Path

if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")
client=anthropic.Anthropic(base_url="https://api.ailoot.ai",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

with client.messages.stream(model='gemini-2.5-pro',max_tokens=1024,messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:
    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:
        for event in stream:
            payload=event.to_dict(mode="json")
            log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush()
            print(json.dumps(payload,ensure_ascii=False))
    final=stream.get_final_message()
    save_result(final.to_dict(mode="json"),"stream-result")
```

### Receive and save results

#### Ailoot · Anthropic Messages

json or SSE

##### Keep all completed results

Keep every complete returned response, file and content part.

Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.

##### If the original response needs checking

Keep request/response IDs and headers. No generic text job retrieval URL is supplied.

Response fields

| Field | Type |
| --- | --- |
| Field`id` | Typestring |
| Field`model` | Typestring |
| Field`content[]` | Typetext\|thinking\|tool\_use\|other content block |
| Field`stop_reason` | Typestring\|null |
| Field`usage` | Typeobject |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |

### Aliases

#### Model aliases

<strong>Ailoot</strong> [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=messages)
**Ailoot Ultra** [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=messages), [`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=messages)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=messages), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=messages), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=messages)

**Ailoot · Gemini generateContent** `POST /v1beta/models/{model}:generateContent` `gemini-2.5-pro`

[`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=gemini)

Google /`gemini-2.5-pro`

### Overview

Gemini 2.5 Pro is Google’s stable thinking model for complex code, mathematics, STEM and long-context analysis. It accepts text, images, audio, video and PDF and returns text, with tools and structured output. Its dynamic reasoning budget supports 128–32,768 tokens and cannot be fully disabled.

Accepted inputs

Text · Images

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot · Gemini generateContent** `POST /v1beta/models/{model}:generateContent`

Input types

`text`, `image`

Output types

`text`

Context

1,048,576 tokens

Maximum output

65,536 tokens

Output format

json or supported streaming

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`path.model` | Type`string` | RequirementRequired | Values & limits gemini-2.5-pro | Default— |
| Field`contents` | Type`content[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— |
| Field`contents[].role` | Type`string` | RequirementOptional | Values & limits user, model | Default— |
| Field`contents[].parts` | Type`part[]` | RequirementRequired | Values & limits | Default— |
| Field`systemInstruction` | Type`content` | RequirementOptional | Values & limits | Default— |
| Field`generationConfig.maxOutputTokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— |
| Field`generationConfig.temperature` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`generationConfig.topP` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`generationConfig.topK` | Type`integer` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`generationConfig.stopSequences` | Type`string[]` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`generationConfig.thinkingConfig.includeThoughts` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`generationConfig.thinkingConfig.thinkingBudget` | Type`integer` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`tools[].functionDeclarations` | Type`function_declaration[]` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`toolConfig.functionCallingConfig.mode` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`safetySettings` | Type`object[]` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`sessionId` | Type`string` | RequirementOptional | Values & limits | Default— |

Input material combinations

**Text** · UTF8 text

`contents[].parts[].text`

**Text + image**

`parts[].inlineData={mimeType,data}`

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`material_types` | Contracttext, image |
| Parameter`required` | Contractcontents |
| Parameter`optional_controls` | Contractnull |
| Parameter`content_type` | Contractapplication/json |
| Parameter`text_file_material` | Contractactual UTF-8 content inserted as text; file IDs/URLs need separate exact support |

Lifecycle: `exact retained published method`

Method shapes and IDs are exact; supplier capability is separate from admission.

### Pricing

#### Ailoot method rates

Input

$0.00125 */ 1K*

Output

$0.01 */ 1K*

Cache read

$0.000125 */ 1K*

#### Prices by request length · Gemini generateContent

| Request size, tokens | Input | Output | Cache read | Cache write | 5 min cache | 1 hour cache |
| --- | --- | --- | --- | --- | --- | --- |
| Request size, tokens(0; 200,000\] | Input$0.00125 | Output$0.01 | Cache read$0.000125 | Cache writeBase: — | 5 min cacheBase: — | 1 hour cacheBase: — |
| Request size, tokens(200,000; ∞) | Input$0.0025 | Output$0.015 | Cache read$0.00025 | Cache writeBase: — | 5 min cacheBase: — | 1 hour cacheBase: — |

Rates in USD per 1K tokens. If no rate is set, the base rate for this method is inherited; «—» means no base rate is set.

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

#### Reference tariff details

Model-level reference schedules do not change method selection, quotes or charges. Active charges use the selected Ailoot method rates.

Model reference schedules

#### Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

| Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge |
| --- | --- | --- | --- | --- |
| ConfigurationOpenAI Chat · Base token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens Output · Reasoning output tokens **$0.02** / 1K tokens |
| ConfigurationOpenAI Chat · Request-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationOpenAI Chat · Request-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationAnthropic Messages · Base token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens Output · Reasoning output tokens **$0.02** / 1K tokens |
| ConfigurationAnthropic Messages · Request-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationAnthropic Messages · Request-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

### Example requests

#### Ailoot · Gemini generateContent

Text exampleImage inputPython SDKNode.js SDKPython stream

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"
export AILOOT_TEXT_FILE
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"contents": []}')
f=Path(os.environ["AILOOT_TEXT_FILE"])
if not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")
text=f.read_text(encoding="utf-8")
if not text.strip():raise SystemExit("Source material must contain text")
p["contents"]=[{"role":"user","parts":[{"text":"Summarize this material and quote supporting source passages.\n\n"+text}]}]
Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1beta/models/gemini-2.5-pro:generateContent \
  -H "x-goog-api-key: $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

save_result(json.loads(Path("result.json").read_text(encoding="utf-8")))
PY_RESULT
```

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"
export AILOOT_IMAGE_FILE
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"contents": [{"role": "user", "parts": [{"text": "Read labels and numbers in this image; flag unreadable text."}]}]}')
import base64
f=Path(os.environ["AILOOT_IMAGE_FILE"])
if not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")
raw=f.read_bytes()
mime="image/png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "image/jpeg" if raw.startswith(b"\xff\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None
if not mime:raise SystemExit("Use PNG JPEG or WebP")
b64=base64.b64encode(raw).decode()
p["contents"][0]["parts"].append({"inlineData":{"mimeType":mime,"data":b64}})
Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1beta/models/gemini-2.5-pro:generateContent \
  -H "x-goog-api-key: $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

save_result(json.loads(Path("result.json").read_text(encoding="utf-8")))
PY_RESULT
```

```python
from google import genai
from google.genai import types
import os

if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")
client = genai.Client(
    api_key=os.environ["AILOOT_API_KEY"],
    http_options=types.HttpOptions(base_url="https://api.ailoot.ai"),
)
resp = client.models.generate_content(model="gemini-2.5-pro", contents="Explain the difference between an observation and a hypothesis in three sentences.")
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

save_result(resp.to_json_dict())
```

```js
import { GoogleGenAI } from "@google/genai";

if (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");
const ai = new GoogleGenAI({ apiKey: process.env.AILOOT_API_KEY, httpOptions: { baseUrl: "https://api.ailoot.ai" } });
const resp = await ai.models.generateContent({ model: "gemini-2.5-pro", contents: "Explain the difference between an observation and a hypothesis in three sentences." });
import { writeFileSync } from "node:fs";

function saveResult(data, stem = "result") {
  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));
  console.log(JSON.stringify(data, null, 2));
  const saveBlob = (encoded, suffix, label) => {
    const raw = Buffer.from(encoded, "base64");
    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;
    const file = `${stem}-${label}.${ext}`;
    writeFileSync(file, raw); console.log("Saved", file);
  };
  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));
  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));
  for (const [i, item] of (data.output || []).entries()) {
    console.log("Output", i, JSON.stringify(item));
    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);
  }
  for (const [ci, candidate] of (data.candidates || []).entries()) {
    for (const [pi, part] of (candidate.content?.parts || []).entries()) {
      console.log("Candidate/part", ci, pi, JSON.stringify(part));
      const blob = part.inlineData || part.inline_data;
      if (blob?.data) {
        const mime = blob.mimeType || blob.mime_type;
        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";
        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);
      }
    }
  }
}

saveResult(resp);
```

```python
from google import genai
from google.genai import types
import os
from pathlib import Path

if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")
client=genai.Client(api_key=os.environ["AILOOT_API_KEY"],http_options=types.HttpOptions(base_url="https://api.ailoot.ai"))
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

count=0
with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:
    for chunk in client.models.generate_content_stream(model='gemini-2.5-pro',contents="Explain observations and hypotheses in three sentences."):
        payload=chunk.to_json_dict()
        log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush()
        save_result(payload,"stream-chunk-"+str(count))
        count+=1
```

### Receive and save results

#### Ailoot · Gemini generateContent

json or supported streaming

##### Keep all completed results

Keep every complete returned response, file and content part.

Keep all candidates and parts, including function calls, thought signatures and usage; assemble stream chunks in order.

##### If the original response needs checking

Keep request/response IDs and headers. No generic text job retrieval URL is supplied.

Response fields

| Field | Type |
| --- | --- |
| Field`responseId` | Typestring |
| Field`modelVersion` | Typestring |
| Field`candidates[].content.parts[]` | Typetext\|inlineData\|functionCall\|other part |
| Field`candidates[].finishReason` | Typestring |
| Field`usageMetadata` | Typeobject |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |

### Aliases

#### Model aliases

<strong>Ailoot</strong> [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=gemini)
**Ailoot Ultra** [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro), [`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=gemini), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro)

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `gemini-2.5-pro`

[`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=chat)

Google /`gemini-2.5-pro`

Model ID

- `gemini-2.5-pro`
- `google/gemini-2.5-pro`

### Overview

Gemini 2.5 Pro is Google’s stable thinking model for complex code, mathematics, STEM and long-context analysis. It accepts text, images, audio, video and PDF and returns text, with tools and structured output. Its dynamic reasoning budget supports 128–32,768 tokens and cannot be fully disabled.

Accepted inputs

Text

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions`

Input types

`text`

Output types

`text`

Output format

json or SSE

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits gemini-2.5-pro | Default— |
| Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— |
| Field`messages[].role` | Type`string` | RequirementRequired | Values & limits Model-specific | Default— |
| Field`messages[].content` | Type`string` | RequirementOptional | Values & limits Applies when: Text conversation | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse |

Input material combinations

**Text** · UTF8 text

`messages[].content`

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractmodel, messages |
| Parameter`material_types` | Contracttext |
| Parameter`messages` | Contractmessage array with role/content shape |
| Parameter`file_material` | Contractactual UTF-8 document inserted as literal text; no file ID inferred |
| Parameter`optional_controls` | Contractstream |
| Parameter`control_scope` | ContractText conversation; stream is a boolean and defaults to false. |
| Parameter`output_modalities` | Contracttext |
| Parameter`hosted_operations` | Contractfalse |
| Parameter`multimodal_input_binding` | Contractnull |

Method aliases: `/chat/completions`

Lifecycle: `synchronous_or_streamed`

Send exact model ID with messages.

Context length is not an output cap.

A text file may supply literal text; image/audio/file-object inputs need exact binding.

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Standard rate When fast mode is selected

Flex mode

Standard rate When flex mode is selected

Maximum reasoning effort

Standard rate When maximum reasoning effort uses the default adjustment

Explicit cache pricing

Not enabled When explicit cache is requested

Reasoning output

Reasoning uses the listed subset rate within aggregate output; do not add those tokens twice. When output includes reasoning tokens

#### Ailoot rates

#### Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

| Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge |
| --- | --- | --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens Output · Reasoning output tokens **$0.02** / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · OpenAI Chat

curlPython SDK

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model":"gemini-2.5-pro","messages":[{"role":"user","content":"hello"}],"stream":false}')

Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path
r=json.loads(Path("result.json").read_text())
for x in r.get("choices",[]):
    if x.get("message",{}).get("content"): print(x["message"]["content"])
PY_RESULT
```

```python
from openai import OpenAI
import os

if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")
client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)
result=client.chat.completions.create(model="gemini-2.5-pro", messages=[{"role":"user","content":"hello"}], stream=False)
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

save_result(result.to_dict(mode="json"))
```

### Receive and save results

#### Ailoot Ultra · OpenAI Chat

json or SSE

##### Keep all completed results

Keep every complete returned response, file and content part.

Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.

##### If the original response needs checking

Keep request/response IDs and headers. No generic text job retrieval URL is supplied.

Response fields

| Field | Type |
| --- | --- |
| Field`choices[].index` | Typeinteger |
| Field`choices[].message.content` | Typestring\|null |
| Field`choices[].message.tool_calls` | Typetool\_call\[\] |
| Field`choices[].message.reasoning_content` | Typestring |
| Field`choices[].message.reasoning_details` | Typeobject\|array |
| Field`choices[].finish_reason` | Typestring\|null |
| Field`usage` | Typeobject |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |

### Aliases

#### Model aliases

<strong>Ailoot</strong> [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro)
**Ailoot Ultra** [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=chat), [`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=chat)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=chat), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=chat)

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `gemini-2.5-pro`

[`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=messages)

Google /`gemini-2.5-pro`

Model ID

- `gemini-2.5-pro`
- `google/gemini-2.5-pro`

### Overview

Gemini 2.5 Pro is Google’s stable thinking model for complex code, mathematics, STEM and long-context analysis. It accepts text, images, audio, video and PDF and returns text, with tools and structured output. Its dynamic reasoning budget supports 128–32,768 tokens and cannot be fully disabled.

Accepted inputs

Text

Results

json · sse

### Available in Ailoot · inputs & methods

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages`

Input types

`text`

Output types

`json`, `sse`

Output format

JSON or SSE

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits gemini-2.5-pro | Default— |
| Field`messages` | Type`message[]` | RequirementRequired | Values & limits | Default— |
| Field`messages[].role` | Type`string` | RequirementRequired | Values & limits user, assistant | Default— |
| Field`messages[].content` | Type`string` | RequirementRequired | Values & limits | Default— |
| Field`max_tokens` | Type`integer` | RequirementRequired | Values & limits | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse |

Input material combinations

**Text** · UTF-8 text

`messages[].content string`

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractmodel, messages, max\_tokens |
| Parameter`optional_controls` | Contractstream |
| Parameter`material_types` | Contracttext |
| Parameter`text_file_material` | ContractRead the actual UTF-8 document and put its text in the indicated input or message content string. |

Lifecycle: `synchronous_or_streamed`

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Standard rate When fast mode is selected

Flex mode

Standard rate When flex mode is selected

Maximum reasoning effort

Standard rate When maximum reasoning effort uses the default adjustment

Explicit cache pricing

Not enabled When explicit cache is requested

Reasoning output

Reasoning uses the listed subset rate within aggregate output; do not add those tokens twice. When output includes reasoning tokens

#### Ailoot rates

#### Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

| Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge |
| --- | --- | --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens Output · Reasoning output tokens **$0.02** / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · Anthropic Messages

Complete minimal JSON bodycurl · use your UTF-8 documentPython · save the complete result

```json
{
  "model": "gemini-2.5-pro",
  "max_tokens": 128,
  "messages": [
    {
      "role": "user",
      "content": "Summarize the incident report."
    }
  ],
  "stream": false
}
```

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}"
export AILOOT_TEXT_FILE
python3 - <<'PY_REQUEST'
import json, os
from pathlib import Path

source_file = Path(os.environ['AILOOT_TEXT_FILE'])
if not source_file.is_file():
    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')
text = source_file.read_text(encoding='utf-8')
if not text.strip():
    raise SystemExit('Choose a document containing text')
payload = {'model': 'gemini-2.5-pro', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}
payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text
Path('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \
  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path

result = json.loads(Path('result.json').read_text(encoding='utf-8'))
print(json.dumps(result, ensure_ascii=False, indent=2))
PY_RESULT
```

```python
import json, os
from pathlib import Path

source_file = Path(os.environ['AILOOT_TEXT_FILE'])
if not source_file.is_file():
    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')
text = source_file.read_text(encoding='utf-8')
if not text.strip():
    raise SystemExit('Choose a document containing text')
payload = {'model': 'gemini-2.5-pro', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}
payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text
from urllib.request import Request, urlopen
from urllib.error import HTTPError

api_key = os.environ['AILOOT_API_KEY']
if not api_key.strip():
    raise SystemExit('Set AILOOT_API_KEY before making a request')
headers = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}
headers['x-api-key'] = api_key
request = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')
try:
    with urlopen(request, timeout=120) as response:
        raw = response.read()
        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')
except HTTPError as error:
    Path('result.json').write_bytes(error.read())
    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')
    raise
Path('result.json').write_bytes(raw)
import json
from pathlib import Path

result = json.loads(Path('result.json').read_text(encoding='utf-8'))
print(json.dumps(result, ensure_ascii=False, indent=2))
```

### Receive and save results

#### Ailoot Ultra · Anthropic Messages

JSON or SSE

##### Keep all completed results

Keep every complete returned response, file and content part.

Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.

##### If the original response needs checking

Keep request/response IDs and headers. No generic text job retrieval URL is supplied.

Response fields

| Field | Type |
| --- | --- |
| Field`id` | Typestring |
| Field`model` | Typestring |
| Field`content[]` | Typetext\|thinking\|tool\_use\|other content block |
| Field`stop_reason` | Typestring\|null |
| Field`usage` | Typeobject |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |

### Aliases

#### Model aliases

<strong>Ailoot</strong> [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=messages)
**Ailoot Ultra** [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=messages), [`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=messages)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=messages), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=messages), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=messages)

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `google/gemini-2.5-pro`

[`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=chat)

Google /`google/gemini-2.5-pro`

Model ID

- `gemini-2.5-pro`
- `google/gemini-2.5-pro`

### Overview

Gemini 2.5 Pro is Google’s stable thinking model for complex code, mathematics, STEM and long-context analysis. It accepts text, images, audio, video and PDF and returns text, with tools and structured output. Its dynamic reasoning budget supports 128–32,768 tokens and cannot be fully disabled.

Accepted inputs

Text

Results

Text

### Available in Ailoot · inputs & methods

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions`

Input types

`text`

Output types

`text`

Output format

json or SSE

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits google/gemini-2.5-pro | Default— |
| Field`messages` | Type`message[]` | RequirementRequired | Values & limits Minimum items: 1 | Default— |
| Field`messages[].role` | Type`string` | RequirementRequired | Values & limits Examples: system, user, assistant, tool, function Conditions: These roles are explicitly represented by Source compatibility types; the exact model role set remains model-specific. Model-specific | Default— |
| Field`messages[].content` | Type`string\|content_part[]\|null` | RequirementOptional | Values & limits | Default— |
| Field`messages[].tool_calls` | Type`tool_call[]` | RequirementOptional | Values & limits | Default— |
| Field`messages[].tool_call_id` | Type`string` | RequirementOptional | Values & limits Applies when: role=tool; use actual returned ID | Default— |
| Field`messages[].name` | Type`string` | RequirementOptional | Values & limits | Default— |
| Field`messages[].reasoning_content` | Type`string` | RequirementOptional | Values & limits Applies when: Round-trip actual returned reasoning where this model uses it | Default— |
| Field`messages[].reasoning_details` | Type`object\|array` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`max_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— |
| Field`max_completion_tokens` | Type`integer` | RequirementOptional | Values & limits Minimum: 1 Model-specific | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse |
| Field`stream_options.include_usage` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`temperature` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`top_p` | Type`number` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`stop` | Type`string\|string[]` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`tools` | Type`function_tool[]` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`tools[].type` | Type`string` | RequirementOptional | Values & limits function Model-specific | Default— |
| Field`tools[].function.name` | Type`string` | RequirementRequired | Values & limits Applies when: function tool supplied | Default— |
| Field`tools[].function.description` | Type`string` | RequirementOptional | Values & limits | Default— |
| Field`tools[].function.parameters` | Type`JSON_schema` | RequirementOptional | Values & limits | Default— |
| Field`tool_choice` | Type`string\|object` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`parallel_tool_calls` | Type`boolean` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`response_format` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`reasoning_effort` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`reasoning` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`service_tier` | Type`string` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`instructions` | Type`string` | RequirementOptional | Values & limits Compatibility field | Default— |
| Field`functions` | Type`function[]` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`function_call` | Type`string\|object` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`prompt_cache_options` | Type`object` | RequirementOptional | Values & limits Model-specific | Default— |
| Field`modalities` | Type`string[]` | RequirementOptional | Values & limits text | Default— |
| Field`provider` | Type`object` | RequirementOptional | Values & limits Conditions: provider.options is rejected on this Ultra text route | Default— |
| Field`cache_control.ttl` | Type`string` | RequirementOptional | Values & limits Conditions: 1h is rejected in actual prompt-cache locations | Default— |

Input material combinations

**Text** · UTF8 text

`messages[].content`

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractmodel, messages |
| Parameter`material_types` | Contracttext |
| Parameter`messages` | Contractmessage array with role/content shape |
| Parameter`file_material` | Contractactual UTF-8 document inserted as literal text; no file ID inferred |
| Parameter`optional_controls` | Contractstream, temperature, top\_p, stop, max\_tokens, max\_completion\_tokens, reasoning, response\_format, tools, tool\_choice |
| Parameter`control_scope` | Contractmodel-specific; user function tools differ from hosted tools |
| Parameter`output_modalities` | Contracttext |
| Parameter`hosted_operations` | Contractfalse |
| Parameter`multimodal_input_binding` | Contractnull |

Lifecycle: `synchronous_or_streamed`

Send exact model ID with messages.

Context length is not an output cap.

A text file may supply literal text; image/audio/file-object inputs need exact binding.

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Standard rate When fast mode is selected

Flex mode

Standard rate When flex mode is selected

Maximum reasoning effort

Standard rate When maximum reasoning effort uses the default adjustment

Explicit cache pricing

Not enabled When explicit cache is requested

Reasoning output

Reasoning uses the listed subset rate within aggregate output; do not add those tokens twice. When output includes reasoning tokens

#### Ailoot rates

#### Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

| Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge |
| --- | --- | --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens Output · Reasoning output tokens **$0.02** / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · OpenAI Chat

curlPython SDKPython stream

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model": "google/gemini-2.5-pro", "messages": [{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}]}')

Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path
r=json.loads(Path("result.json").read_text())
for x in r.get("choices",[]):
    if x.get("message",{}).get("content"): print(x["message"]["content"])
PY_RESULT
```

```python
from openai import OpenAI
import os

if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")
client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)
result=client.chat.completions.create(model='google/gemini-2.5-pro',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}])
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

save_result(result.to_dict(mode="json"))
```

```python
from openai import OpenAI
import os
from pathlib import Path

if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")
client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)
import base64, json
from pathlib import Path

def save_result(data, stem="result"):
    # Keep every field, including usage, IDs, reasoning and tool requests.
    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(data, ensure_ascii=False, indent=2))
    def save_blob(encoded, suffix, label):
        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)
        ext = "png" if raw.startswith(b"\x89PNG\r\n\x1a\n") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix
        file = Path(stem + "-" + label + "." + ext)
        file.write_bytes(raw)
        print("Saved", file)
    for index, block in enumerate(data.get("content") or []):
        print("Content", index, json.dumps(block, ensure_ascii=False))
    for choice in data.get("choices") or []:
        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))
    for index, item in enumerate(data.get("output") or []):
        print("Output", index, json.dumps(item, ensure_ascii=False))
        if item.get("type") == "image_generation_call" and item.get("result"):
            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))
    for ci, candidate in enumerate(data.get("candidates") or []):
        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):
            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))
            blob = part.get("inlineData") or part.get("inline_data")
            if blob and blob.get("data"):
                mime = blob.get("mimeType") or blob.get("mime_type")
                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")
                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))

with client.chat.completions.stream(model='google/gemini-2.5-pro',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:
    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:
        for event in stream:
            payload=event.to_dict(mode="json")
            log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush()
            print(json.dumps(payload,ensure_ascii=False))
    final=stream.get_final_completion()
    save_result(final.to_dict(mode="json"),"stream-result")
```

### Receive and save results

#### Ailoot Ultra · OpenAI Chat

json or SSE

##### Keep all completed results

Keep every complete returned response, file and content part.

Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.

##### If the original response needs checking

Keep request/response IDs and headers. No generic text job retrieval URL is supplied.

Response fields

| Field | Type |
| --- | --- |
| Field`choices[].index` | Typeinteger |
| Field`choices[].message.content` | Typestring\|null |
| Field`choices[].message.tool_calls` | Typetool\_call\[\] |
| Field`choices[].message.reasoning_content` | Typestring |
| Field`choices[].message.reasoning_details` | Typeobject\|array |
| Field`choices[].finish_reason` | Typestring\|null |
| Field`usage` | Typeobject |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |

### Aliases

#### Model aliases

<strong>Ailoot</strong> [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro)
**Ailoot Ultra** [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=chat), [`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=chat)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=chat), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=chat)

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `google/gemini-2.5-pro`

[`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=messages)

Google /`google/gemini-2.5-pro`

Model ID

- `gemini-2.5-pro`
- `google/gemini-2.5-pro`

### Overview

Gemini 2.5 Pro is Google’s stable thinking model for complex code, mathematics, STEM and long-context analysis. It accepts text, images, audio, video and PDF and returns text, with tools and structured output. Its dynamic reasoning budget supports 128–32,768 tokens and cannot be fully disabled.

Accepted inputs

Text

Results

json · sse

### Available in Ailoot · inputs & methods

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages`

Input types

`text`

Output types

`json`, `sse`

Output format

JSON or SSE

| Field | Type | Requirement | Values & limits | Default |
| --- | --- | --- | --- | --- |
| Field`model` | Type`string` | RequirementRequired | Values & limits google/gemini-2.5-pro | Default— |
| Field`messages` | Type`message[]` | RequirementRequired | Values & limits | Default— |
| Field`messages[].role` | Type`string` | RequirementRequired | Values & limits user, assistant | Default— |
| Field`messages[].content` | Type`string` | RequirementRequired | Values & limits | Default— |
| Field`max_tokens` | Type`integer` | RequirementRequired | Values & limits | Default— |
| Field`stream` | Type`boolean` | RequirementOptional | Values & limits | Defaultfalse |

Input material combinations

**Text** · UTF-8 text

`messages[].content string`

Method parameters and lifecycle

| Parameter | Contract |
| --- | --- |
| Parameter`content_type` | Contractapplication/json |
| Parameter`required` | Contractmodel, messages, max\_tokens |
| Parameter`optional_controls` | Contractstream |
| Parameter`material_types` | Contracttext |
| Parameter`text_file_material` | ContractRead the actual UTF-8 document and put its text in the indicated input or message content string. |

Lifecycle: `synchronous_or_streamed`

### Pricing

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode

Standard rate When fast mode is selected

Flex mode

Standard rate When flex mode is selected

Maximum reasoning effort

Standard rate When maximum reasoning effort uses the default adjustment

Explicit cache pricing

Not enabled When explicit cache is requested

Reasoning output

Reasoning uses the listed subset rate within aggregate output; do not add those tokens twice. When output includes reasoning tokens

#### Ailoot rates

#### Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

| Configuration | Rate schedule | Context tokens, more than | Context tokens, up to and including | Charge |
| --- | --- | --- | --- | --- |
| ConfigurationBase token rates | Rate scheduleBase rate | Context tokens, more than— | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens Output · Reasoning output tokens **$0.02** / 1K tokens |
| ConfigurationRequest-length tier 1 | Rate schedule— | Context tokens, more than0 | Context tokens, up to and including200,000 | Charge Input · Input tokens **$0.0025** / 1K tokens Output · Output tokens **$0.02** / 1K tokens Input · Cache read **$0.00025** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |
| ConfigurationRequest-length tier 2 | Rate schedule— | Context tokens, more than200,000 | Context tokens, up to and includingNo upper bound | Charge Input · Input tokens **$0.005** / 1K tokens Output · Output tokens **$0.03** / 1K tokens Input · Cache read **$0.0005** / 1K tokens Input · Cache write **$0.00075** / 1K tokens Input · Cache write, 1 hour **—** / 1K tokens |

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. [How reservation and settlement work →](https://ailoot.ai/docs/en/billing/reserve/)

### Example requests

#### Ailoot Ultra · Anthropic Messages

Complete minimal JSON bodycurl · use your UTF-8 documentPython · save the complete result

```json
{
  "model": "google/gemini-2.5-pro",
  "max_tokens": 128,
  "messages": [
    {
      "role": "user",
      "content": "Summarize the incident report."
    }
  ],
  "stream": false
}
```

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}"
export AILOOT_TEXT_FILE
python3 - <<'PY_REQUEST'
import json, os
from pathlib import Path

source_file = Path(os.environ['AILOOT_TEXT_FILE'])
if not source_file.is_file():
    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')
text = source_file.read_text(encoding='utf-8')
if not text.strip():
    raise SystemExit('Choose a document containing text')
payload = {'model': 'google/gemini-2.5-pro', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}
payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text
Path('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \
  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import json
from pathlib import Path

result = json.loads(Path('result.json').read_text(encoding='utf-8'))
print(json.dumps(result, ensure_ascii=False, indent=2))
PY_RESULT
```

```python
import json, os
from pathlib import Path

source_file = Path(os.environ['AILOOT_TEXT_FILE'])
if not source_file.is_file():
    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')
text = source_file.read_text(encoding='utf-8')
if not text.strip():
    raise SystemExit('Choose a document containing text')
payload = {'model': 'google/gemini-2.5-pro', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}
payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text
from urllib.request import Request, urlopen
from urllib.error import HTTPError

api_key = os.environ['AILOOT_API_KEY']
if not api_key.strip():
    raise SystemExit('Set AILOOT_API_KEY before making a request')
headers = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}
headers['x-api-key'] = api_key
request = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')
try:
    with urlopen(request, timeout=120) as response:
        raw = response.read()
        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')
except HTTPError as error:
    Path('result.json').write_bytes(error.read())
    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')
    raise
Path('result.json').write_bytes(raw)
import json
from pathlib import Path

result = json.loads(Path('result.json').read_text(encoding='utf-8'))
print(json.dumps(result, ensure_ascii=False, indent=2))
```

### Receive and save results

#### Ailoot Ultra · Anthropic Messages

JSON or SSE

##### Keep all completed results

Keep every complete returned response, file and content part.

Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.

##### If the original response needs checking

Keep request/response IDs and headers. No generic text job retrieval URL is supplied.

Response fields

| Field | Type |
| --- | --- |
| Field`id` | Typestring |
| Field`model` | Typestring |
| Field`content[]` | Typetext\|thinking\|tool\_use\|other content block |
| Field`stop_reason` | Typestring\|null |
| Field`usage` | Typeobject |

Errors and next steps

| Response | Condition | Next step |
| --- | --- | --- |
| Response400 · `invalid_request_error` | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |

### Aliases

#### Model aliases

<strong>Ailoot</strong> [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=messages)
**Ailoot Ultra** [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=messages), [`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=messages)

#### Method path aliases

`/chat/completions`

#### Related caller IDs

[`google/gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=google%2Fgemini-2.5-pro&fmt=messages), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Core&caller=gemini-2.5-pro&fmt=messages), [`gemini-2.5-pro`](https://ailoot.ai/models/en/#m=google%2Fgemini-2.5-pro&route=Ultra&caller=gemini-2.5-pro&fmt=messages)

FAQ · Google: Gemini 2.5 Pro

What inputs and results are available?

`POST /v1/messages` · `gemini-2.5-pro`: `text`, `image` → `text` `POST /v1beta/models/{model}:generateContent` · `gemini-2.5-pro`: `text`, `image` → `text` `POST /v1/chat/completions` · `gemini-2.5-pro`: `text` → `text` `POST /v1/messages` · `gemini-2.5-pro`: `text` → `json`, `sse` `POST /v1/chat/completions` · `google/gemini-2.5-pro`: `text` → `text` `POST /v1/messages` · `google/gemini-2.5-pro`: `text` → `json`, `sse`

Which fields does the request use?

`POST /v1/messages` · `gemini-2.5-pro`: `model`, `messages`, `system`, `max_tokens`, `stream`, `metadata` `POST /v1beta/models/{model}:generateContent` · `gemini-2.5-pro`: `contents`, `systemInstruction`, `sessionId` `POST /v1/chat/completions` · `gemini-2.5-pro`: `model`, `messages`, `stream` `POST /v1/messages` · `gemini-2.5-pro`: `model`, `messages`, `max_tokens`, `stream` `POST /v1/chat/completions` · `google/gemini-2.5-pro`: `model`, `messages`, `stream`, `modalities`, `provider` `POST /v1/messages` · `google/gemini-2.5-pro`: `model`, `messages`, `max_tokens`, `stream`

What limits apply?

`POST /v1/messages` · `gemini-2.5-pro`: `ctx`: `1048576`; `max_out`: `65536`; `messages.min_items`: `1`; `max_tokens.minimum`: `1` `POST /v1beta/models/{model}:generateContent` · `gemini-2.5-pro`: `ctx`: `1048576`; `max_out`: `65536`; `contents.min_items`: `1` `POST /v1/chat/completions` · `gemini-2.5-pro`: `messages.min_items`: `1` `POST /v1/chat/completions` · `google/gemini-2.5-pro`: `messages.min_items`: `1`

Connect Ailoot to Claude Code, OpenCode, Hermes or your own app.

## The company and its project portfolio

The company and its project portfolio: millions of customers; monthly sales in the billions.

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Subscription discounts for regular use. Promo codes offer up to 50% off token purchases.

Subscription

Choose a discounted plan for your regular requests.

Promo code: up to 50% off

Enter your code at checkout. The price updates to reflect the current promotion.

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The model, tokens and amount are recorded for each request.

[Choose a subscription](https://ailoot.ai/docs/en/billing/subscriptions/) · [View model prices](https://ailoot.ai/models/en/)

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The service offer, licence agreement and data processing policy are available before you connect.

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## Ailoot · The company and its project portfolio





Ailoot combines established operating experience, a large client base, stable service and ongoing KPI control.





The company and its project portfolio: millions of customers; monthly sales in the billions.





Ailoot brings that operating experience to API access for AI features in customer products, agents, applications and automations.