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Kimi K3.1 Pro

Kimi K3.1 Pro is Moonshot AI's flagship model for agentic coding, tool use and work over long documents, released on October 23, 2026. It thinks before it answers, reads text and images, calls your function tools and holds a 1M-token context. Call it with the OpenAI SDK or with the native FlyMy.AI API, on the same wallet as every other model, or pick it as your agent's brain.

Endpoint idflymyai/kimi-k3_1-pro
Model pagehttps://app.flymy.ai/models/flymyai/kimi-k3_1-pro
OpenAI base_urlhttps://api.flymy.ai/api/v1/flymyai/kimi-k3_1-pro/openai/v1
Native routePOST https://api.flymy.ai/api/v1/flymyai/kimi-k3_1-pro/predict
Agent model idkimi-k3.1-pro

OpenAI-compatible API​

from openai import OpenAI

client = OpenAI(
    base_url="https://api.flymy.ai/api/v1/flymyai/kimi-k3_1-pro/openai/v1",
    api_key="fly-***",
)

response = client.chat.completions.create(
    model="kimi-k3.1-pro",
    messages=[
        {"role": "system", "content": "Answer briefly."},
        {"role": "user", "content": "Write a Python one-liner that reverses a string."},
    ],
    reasoning_effort="low",
    max_tokens=2000,
)

print(response.choices[0].message.content)
print(response.usage)

The model is selected by the base_url; model is echoed back. The key is your FlyMy.AI key as a Bearer token. Leave out temperature and top_p: the model sets its own (see Parameters).

With stream=True, the answer arrives as one content chunk when the model has finished, followed by a chunk with finish_reason, the usage chunk and data: [DONE].

usage follows the OpenAI convention: completion_tokens includes the reasoning tokens, itemized in completion_tokens_details.reasoning_tokens; prompt_tokens_details.cached_tokens shows the part of the prompt read from the cache, and usage.cost is the price of the call.

Function tools​

tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Current weather for a city",
        "parameters": {
            "type": "object",
            "properties": {"city": {"type": "string"}},
            "required": ["city"],
        },
    },
}]
messages = [{"role": "user", "content": "What's the weather in Paris right now?"}]

first = client.chat.completions.create(
    model="kimi-k3.1-pro", messages=messages, tools=tools
)
call = first.choices[0].message.tool_calls[0]
messages += [
    first.choices[0].message,
    {"role": "tool", "tool_call_id": call.id, "content": '{"temp_c": 14, "sky": "light rain"}'},
]
final = client.chat.completions.create(
    model="kimi-k3.1-pro", messages=messages, tools=tools
)
print(final.choices[0].message.content)

tool_choice takes auto (the default) or required. Kimi K3.1 Pro does not take a named function in tool_choice: to make it call one tool, send only that tool with tool_choice="required". Send the assistant message with its tool_calls back as it came, then one tool message per call.

Priority tier​

Set service_tier="priority" (or "nitro") for Moonshot's faster Highspeed serving at the priority price. Without it the call runs on the default tier. The response's service_tier says which tier answered.

Native API​

The native route takes form fields or a JSON body and answers with one Server-Sent Event carrying the result:

curl -X POST https://api.flymy.ai/api/v1/flymyai/kimi-k3_1-pro/predict \
  -H "X-API-KEY: fly-***" -H "Content-Type: application/json" \
  -d '{"prompt": "Write a haiku about rain.", "reasoning_effort": "low"}'

output_data holds output (the answer), finish_reason, model, service_tier, stream_details (input_tokens, output_tokens, cached_tokens, reasoning_tokens), reasoning when the model shows it, and charge_usd, the price of the call.

Kimi K3.1 Pro does not use /predict/stream/. For long jobs, /predict/async/ works as for other models, except in private mode.

Parameters​

ParameterValues
promptOne user message
messagesChat history in the Chat Completions format (a JSON array in form data); used instead of prompt. Text and image_url content parts
system_promptInstructions for the whole chat, added unless messages already has a system message
reasoning_effortnone (answers at once), low, medium (default) or high
service_tierdefault or priority (alias nitro)
max_tokensMost tokens to generate, reasoning included, 1 to 943,718 (max_completion_tokens works too)
private_modetrue keeps the prompt and the answer out of FlyMyAI storage and logs

The model sets its own temperature and top_p. Leave them out: sent together with tools, they make the call fail; without tools they have no effect.

The OpenAI-compatible route also accepts up to 128 function tools, tool_choice (auto or required) and tool-result messages. response_format is rejected with 400 unsupported_parameter.

Repeated prompt content is read from the cache by itself and billed at the cached rate. Keep the system prompt and tool definitions first and unchanged across turns; the first call with a new prefix is billed in full.

Private mode​

Send private_mode: true - extra_body={"private_mode": True} in the OpenAI SDK, or a form or JSON field on the native route. FlyMy.AI then keeps neither the prompt nor the answer: the request history shows the call, its token counts and its price, without the text. Private mode works with synchronous calls only; an async request with it is refused, because an async request is replayed from storage.

The host that serves the call keeps its own retention policy.

From an AI assistant​

An assistant connected to FlyMy.AI quotes Kimi K3.1 Pro with get_pricing, which also returns its OpenAI base_url, and asks it with run_model (endpoint_id: flymyai/kimi-k3_1-pro, the same input as /predict). The result is the answer as text, followed by its token counts and charge_usd.

Use Kimi as your agent's brain​

Choose Kimi K3.1 Pro in the agent model picker, pass "model": "kimi-k3.1-pro" on the REST API, or pass model: "kimi-k3.1-pro" to create_agent or update_agent on the Agents MCP. list_agent_models lists its reasoning levels: low, medium (the default), high and max. Each model call is debited from the agent owner's FlyMy balance as it completes, at the default tier's prices; you do not need a Moonshot key.

Pricing​

TierInputCached inputOutput
Default$2 / 1M$0.20 / 1M$10 / 1M
Priority$4 / 1M$0.20 / 1M$20 / 1M

Reasoning tokens are billed as output. The price of every call is in charge_usd (native) or usage.cost (OpenAI-compatible) and in your usage.

Errors​

What you seeMeaning
422 on the OpenAI routeA parameter is out of range, service_tier is not default or priority, or messages is malformed; the message says which
400 unsupported_parameterresponse_format
500 model_error on the OpenAI routeUsually a named function in tool_choice, or temperature or top_p sent with tools: send the one tool with tool_choice="required" and leave the sampling fields out
HTTP 200 with status_code: 400 from /predict/stream/Use /predict or the OpenAI-compatible route
private mode does not support async requestsSend the private call synchronously
403 Insufficient fundsTop up your balance