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Moonshot (Kimi)

Moonshot AI provides an OpenAI-compatible API for its Kimi models — the Kimi K3 and K2 thinking models and the Moonshot v1 generation models. The Moonshot provider extends the OpenAI provider, so all of its options are supported.

Setup​

  1. Get an API key from the Kimi (Moonshot) platform.
  2. Set the MOONSHOT_API_KEY environment variable or specify apiKey in your config.

Kimi K3 requires a successful account top-up of at least $1; see the access requirements.

providers:
  - id: moonshot:kimi-k3

Both moonshot:<model> and moonshot:chat:<model> resolve to the chat completions endpoint. If you omit the model, the provider defaults to kimi-k3.

Available Models​

Moonshot's lineup rotates over time — call the list models API (GET https://api.moonshot.ai/v1/models) for the live set. As of writing:

  • Kimi K3 — flagship thinking model, 1M context: kimi-k3 (released July 2026). Always-on reasoning, native image and video understanding, and a top-level reasoning_effort control (see below).
  • Kimi K2 — thinking models, 256k context: kimi-k2.6, kimi-k2.5, kimi-k2.7-code, kimi-k2.7-code-highspeed. These reason before answering and emit a separate reasoning stream (see below).
  • Moonshot v1 — legacy generation models: moonshot-v1-8k, moonshot-v1-32k, moonshot-v1-128k (context-length variants) and the vision variants moonshot-v1-8k-vision-preview / moonshot-v1-32k-vision-preview / moonshot-v1-128k-vision-preview; existing accounts may also see the auto-router moonshot-v1-auto in the list-models API. The moonshot-v1 series and kimi-k2.5 are closed to newly registered users and sunset platform-wide on August 31, 2026.

The older kimi-k2-0711-preview, kimi-k2-0905-preview, kimi-k2-turbo-preview, kimi-k2-thinking, kimi-k2-thinking-turbo, and kimi-latest ids were discontinued in 2026 — Moonshot recommends migrating to kimi-k3.

Configuration​

providers:
  - id: moonshot:kimi-k3 # flagship thinking model — leave sampling params unset
  - id: moonshot:moonshot-v1-8k # legacy generation model — accepts arbitrary sampling
    config:
      temperature: 0.2
      max_tokens: 1024

Configuration Options​

The provider accepts every option the OpenAI provider supports. Commonly used:

  • temperature, max_tokens, top_p, presence_penalty, frequency_penalty
  • stream
  • response_format (JSON mode), tools / tool_choice (function calling)
  • showThinking — set to false to drop a thinking model's reasoning from the graded output (default true)
  • cost, inputCost, outputCost, cacheReadCost — Moonshot ships no built-in price table, so set these to track cost. Every override is in USD per token. Moonshot's official pricing page publishes rates in USD per 1 million tokens, so divide each published rate by 1,000,000 before configuring it. inputCost/outputCost take precedence over the flat cost; cacheReadCost prices cached prompt tokens.

For example, these illustrative per-million rates convert to per-token overrides. Check the official pricing page for the current rates for your model before using them.

providers:
  - id: moonshot:kimi-k3
    config:
      inputCost: 0.000003 # $3.00 per 1M tokens divided by 1,000,000
      cacheReadCost: 0.0000003 # $0.30 per 1M tokens divided by 1,000,000
      outputCost: 0.000015 # $15.00 per 1M tokens divided by 1,000,000
  - id: moonshot:kimi-k2.6
    config:
      inputCost: 0.00000095 # $0.95 per 1M tokens divided by 1,000,000
      cacheReadCost: 0.00000016 # $0.16 per 1M tokens divided by 1,000,000
      outputCost: 0.000004 # $4.00 per 1M tokens divided by 1,000,000

Any other parameter supported by the OpenAI provider is forwarded as-is.

Kimi thinking models​

The kimi-k3 and kimi-k2.x models are reasoning models and behave differently from the moonshot-v1 family:

  • Fixed sampling parameters. Kimi pins temperature (1.0 with thinking on), top_p, n, and the penalties to fixed values and returns a 400 ("invalid temperature: only 1 is allowed for this model") for any other value. The provider therefore does not send promptfoo's default temperature/max_tokens for kimi-* models — leave them unset (recommended) or set temperature: 1. The moonshot-v1 models accept arbitrary sampling values.
  • Reasoning output. Kimi returns a separate reasoning_content stream that promptfoo surfaces with a Thinking: … prefix. Set showThinking: false when you assert on structured output (for example is-json) so the reasoning doesn't contaminate the parsed result.
  • Token budget. Reasoning tokens count against the output budget. When you leave the token limit unset the provider lets Moonshot apply its server default (32k for K2.x, 131k for K3); if you set one, leave generous headroom for the answer. Moonshot's canonical field is max_completion_tokens (max_tokens is a deprecated alias) — the provider sends max_completion_tokens for kimi-* models whichever of the two you configure.
  • Controlling thinking. The two generations use different, mutually exclusive controls:
    • kimi-k3 is always thinking and accepts a top-level reasoning_effort field, which the provider forwards from config.reasoning_effort. Supported values are low, high, and max (the default). Do not send the K2.x thinking parameter to K3 — the API rejects it.
    • kimi-k2.6 and kimi-k2.5 support thinking: { type: disabled } (pass it via config.passthrough); kimi-k2.7-code is always thinking. The thinking parameter is K2.x-only.
    • Setting config.reasoning_effort on a non-K3 model is a configuration error and the provider fails fast with a clear message instead of sending it.
providers:
  - id: moonshot:kimi-k3
    config:
      showThinking: false
      reasoning_effort: max # optional: low, high, or max (default)
  - id: moonshot:kimi-k2.6
    config:
      passthrough:
        thinking: { type: disabled } # K2.x only: turn reasoning off

See the Kimi K3 quickstart and Using Thinking Models for the full behavior matrix.

Vision​

The vision models (moonshot-v1-*-vision-preview) and the multimodal Kimi models (kimi-k3, kimi-k2.5, kimi-k2.6, kimi-k2.7-code, kimi-k2.7-code-highspeed) accept base64-encoded image input using the standard OpenAI image_url content format. Moonshot does not accept remote image URLs — embed images as data: URIs or reference files uploaded to the Kimi platform as ms://<file-id>. Video input is supported by kimi-k3, kimi-k2.6, kimi-k2.7-code, and kimi-k2.7-code-highspeed, referenced the same way after uploading via the files API. See Use the Kimi Vision Model.

Example Usage​

providers:
  - id: moonshot:kimi-k3
  - id: openai:gpt-4o-mini

prompts:
  - 'Summarize the following in one sentence: {{text}}'

tests:
  - vars:
      text: 'Promptfoo is an open-source tool for testing and evaluating LLM apps.'

A runnable comparison lives in examples/provider-moonshot.

API Details​

  • Base URL: https://api.moonshot.ai/v1 (global). China-mainland keys use https://api.moonshot.cn/v1 — point at it with apiBaseUrl, since the global and China platforms issue region-locked keys.
  • OpenAI-compatible chat completions API.
  • Full API documentation.

See Also​

Last updated on by renovate[bot]