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
claude-haiku-4-5-20251001-thinkingOverview
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
| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits claude-haiku-4-5-20251001-thinking | Default— |
Fieldmessages | Typemessage[] | RequirementRequired | Values & limits Minimum items: 1 | Default— |
Fieldmessages[].role | Typestring | RequirementRequired | Values & limits Model-specific | Default— |
Fieldmessages[].content | Typestring | RequirementOptional | Values & limits Applies when: Text conversation | Default— |
Fieldstream | Typeboolean | RequirementOptional | Values & limits | Defaultfalse |
Input material combinations
Text · UTF8 text
messages[].content
Method parameters and lifecycle
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, messages |
Parametermaterial_types | Contracttext |
Parametermessages | Contractmessage array with role/content shape |
Parameterfile_material | Contractactual UTF-8 document inserted as literal text; no file ID inferred |
Parameteroptional_controls | Contractstream |
Parametercontrol_scope | ContractText conversation; stream is a boolean and defaults to false. |
Parameteroutput_modalities | Contracttext |
Parameterhosted_operations | Contractfalse |
Parametermultimodal_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
- 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
| Configuration | Rate schedule | Charge |
|---|---|---|
| ConfigurationBase token rates | Rate scheduleBase rate | Charge Input · Input tokens $0.002 / 1K tokens Output · Output tokens $0.01 / 1K tokens Input · Cache read $0.0002 / 1K tokens Input · Cache write $0.0025 / 1K tokens Input · Cache write, 1 hour — / 1K tokens |
Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
Example requests
Ailoot Ultra · OpenAI Chat
set -eu
: "${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
| Field | Type |
|---|---|
Fieldchoices[].index | Typeinteger |
Fieldchoices[].message.content | Typestring|null |
Fieldchoices[].message.tool_calls | Typetool_call[] |
Fieldchoices[].message.reasoning_content | Typestring |
Fieldchoices[].message.reasoning_details | Typeobject|array |
Fieldchoices[].finish_reason | Typestring|null |
Fieldusage | 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
Ailoot Ultra claude-haiku-4-5-20251001-thinking
Method path aliases
/chat/completions
Related caller IDs
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