models

Anthropic: Claude Haiku 4.5

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Anthropic: Claude Haiku 4.5

Claude Haiku 4.5 is designed for interactive assistants, user support, everyday information processing and work on code. Supports a separate reasoning mode for complex questions.

About the model

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

When a response to every step matters

Anthropic designed Claude Haiku 4.5 for conversational assistants, user service, collaborative coding and prototyping. The model is useful in a cycle where a person asks a question, receives a result and immediately clarifies the next step. According to Anthropic, this version is characterized by low response latency; the actual time depends on the task and application.

Haiku 4.5 is also intended to process large numbers of separate tasks. In an agentic workflow, it can be assigned a specific subtask and its result then passed to the rest of the system. Described uses include coding, reasoning and interface actions. Tool calls and computer control are possible when the application provides the model with the appropriate tools; a single text request does not give it access to a working environment.

Ordinary answers and a manual reasoning budget

For tasks with multiple logical steps, extended thinking is provided: the application explicitly enables reasoning and sets its budget through budget_tokens. When the method supports these settings, the manual budget_tokens budget must be at least 1024 tokens and less than max_tokens to leave room for the final answer. It guides the amount of analysis, while max_tokens limits all output. Haiku 4.5 uses this manual mode specifically: adaptive reasoning and depth control through effort are not supported for this version. Reasoning between successive tool calls is also not supported.

This distinction is useful when choosing a task. Ordinary mode is suited to direct conversation; enabling reasoning gives the model room to work through code or a complex question. The task's content still determines what information needs to be analyzed and how the result should be presented.

Material and version boundaries

The model accepts text and images and returns text. The context window is 200 thousand tokens, and the maximum response is 64 thousand tokens. An image serves as material for analysis alongside the question: the model can explain visible content and connect it to the text prompt. Image input support does not mean that images can be created or edited.

The manufacturer's standard visual input formats are JPEG/PNG/GIF/WebP, using the first frame of an animation. For native analysis, the longer dimension is 1568 pixels, with 1568 visual tokens; larger images are downscaled before analysis. File and parameter support depends on the application's method.

For this version, Anthropic describes a concise, direct conversational style. It is useful to specify the desired level of detail, result format and task constraints beforehand. The reliable built-in knowledge cutoff is February 2025; information about later events must be supplied in the task material or obtained through tools available to the application. Some requests may be declined.

If the method provides sampling settings, temperature and top_p cannot both be set: one of these parameters is selected for this version.

Ailoot Ultra · OpenAI Chat POST /v1/chat/completions claude-haiku-4-5-20251001-thinking

claude-haiku-4-5-20251001-thinking

Anthropic /claude-haiku-4-5-20251001-thinking

Overview

Claude Haiku 4.5 is designed for interactive assistants, user support, everyday information processing and work on code. Supports a separate reasoning mode for complex questions.

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
FieldTypeRequirementValues & limitsDefault
FieldmodelTypestringRequirementRequiredValues & limits
claude-haiku-4-5-20251001-thinking
Default—
FieldmessagesTypemessage[]RequirementRequiredValues & limits
Minimum items: 1
Default—
Fieldmessages[].roleTypestringRequirementRequiredValues & limits
Model-specific
Default—
Fieldmessages[].contentTypestringRequirementOptionalValues & limits
Applies when: Text conversation
Default—
FieldstreamTypebooleanRequirementOptionalValues & limitsDefaultfalse
Input material combinations

Text · UTF8 text

messages[].content

Method parameters and lifecycle
ParameterContract
Parametercontent_typeContractapplication/json
ParameterrequiredContractmodel, messages
Parametermaterial_typesContracttext
ParametermessagesContractmessage array with role/content shape
Parameterfile_materialContractactual UTF-8 document inserted as literal text; no file ID inferred
Parameteroptional_controlsContractstream
Parametercontrol_scopeContractText conversation; stream is a boolean and defaults to false.
Parameteroutput_modalitiesContracttext
Parameterhosted_operationsContractfalse
Parametermultimodal_input_bindingContractnull

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
Not specified When fast mode is selected
Flex mode
Not specified When flex mode is selected
Maximum reasoning effort
Not specified When maximum reasoning effort uses the default adjustment

Ailoot rates

Prices by configuration

ConfigurationRate scheduleCharge
ConfigurationBase token ratesRate scheduleBase rateCharge
Input · Input tokens $0.002 / 1K tokens
Output · Output tokens $0.01 / 1K tokens
Input · Cache read $0.0002 / 1K tokens
Input · Cache write $0.0025 / 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 →

Example requests

Ailoot Ultra · OpenAI Chat

curlPython SDK
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model":"claude-haiku-4-5-20251001-thinking","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
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="claude-haiku-4-5-20251001-thinking", 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
FieldType
Fieldchoices[].indexTypeinteger
Fieldchoices[].message.contentTypestring|null
Fieldchoices[].message.tool_callsTypetool_call[]
Fieldchoices[].message.reasoning_contentTypestring
Fieldchoices[].message.reasoning_detailsTypeobject|array
Fieldchoices[].finish_reasonTypestring|null
FieldusageTypeobject
Errors and next steps
ResponseConditionNext step
Response400 · invalid_request_errorConditionInvalid required fields, material representation or parameter valueNext stepCorrect the indicated fields before a new creation request.

Aliases

Model aliases

Ailoot Ultra claude-haiku-4-5-20251001-thinking

Method path aliases

/chat/completions

Related caller IDs

claude-haiku-4-5-20251001-thinking

FAQ · Anthropic: Claude Haiku 4.5
What inputs and results are available?

POST /v1/chat/completions · claude-haiku-4-5-20251001-thinking: text → text

Which fields does the request use?

POST /v1/chat/completions · claude-haiku-4-5-20251001-thinking: model, messages, stream

What limits apply?

POST /v1/chat/completions · claude-haiku-4-5-20251001-thinking: messages.min_items: 1

More details

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.

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