--- summary: "Use Mistral models and Voxtral transcription with OpenClaw" read_when: - You want to use Mistral models in OpenClaw - You want Voxtral realtime transcription for Voice Call - You need Mistral API key onboarding and model refs title: "Mistral" --- OpenClaw includes a bundled Mistral plugin that registers four contracts: chat completions, media understanding (Voxtral batch transcription), realtime STT for Voice Call (Voxtral Realtime), and memory embeddings (`mistral-embed`). | Property | Value | | ---------------- | ------------------------------------------- | | Provider id | `mistral` | | Plugin | bundled, `enabledByDefault: true` | | Auth env var | `MISTRAL_API_KEY` | | Onboarding flag | `--auth-choice mistral-api-key` | | Direct CLI flag | `--mistral-api-key ` | | API | OpenAI-compatible (`openai-completions`) | | Base URL | `https://api.mistral.ai/v1` | | Default model | `mistral/mistral-large-latest` | | Embedding model | `mistral-embed` | | Voxtral batch | `voxtral-mini-latest` (audio transcription) | | Voxtral realtime | `voxtral-mini-transcribe-realtime-2602` | ## Getting started Create an API key in the [Mistral Console](https://console.mistral.ai/). ```bash openclaw onboard --auth-choice mistral-api-key ``` Or pass the key directly: ```bash openclaw onboard --mistral-api-key "$MISTRAL_API_KEY" ``` ```json5 { env: { MISTRAL_API_KEY: "sk-..." }, agents: { defaults: { model: { primary: "mistral/mistral-large-latest" } } }, } ``` ```bash openclaw models list --provider mistral ``` ## Built-in LLM catalog [Mistral Medium 3.5](https://docs.mistral.ai/models/model-cards/mistral-medium-3-5-26-04) is the current blended Medium model in the bundled catalog: 128B dense weights, text and image input, 256K context, function calling, structured output, coding, and adjustable reasoning through the Chat Completions API. Use `mistral/mistral-medium-3-5` when you want Mistral's newer unified agentic/coding model instead of the default `mistral/mistral-large-latest`. OpenClaw currently ships this bundled Mistral catalog: | Model ref | Input | Context | Max output | Notes | | -------------------------------- | ----------- | ------- | ---------- | ---------------------------------------------------------------- | | `mistral/mistral-large-latest` | text, image | 262,144 | 16,384 | Default model | | `mistral/mistral-medium-2508` | text, image | 262,144 | 8,192 | Mistral Medium 3.1 | | `mistral/mistral-medium-3-5` | text, image | 262,144 | 8,192 | Mistral Medium 3.5; adjustable reasoning | | `mistral/mistral-small-latest` | text, image | 128,000 | 16,384 | Mistral Small 4; adjustable reasoning via API `reasoning_effort` | | `mistral/pixtral-large-latest` | text, image | 128,000 | 32,768 | Pixtral | | `mistral/codestral-latest` | text | 256,000 | 4,096 | Coding | | `mistral/devstral-medium-latest` | text | 262,144 | 32,768 | Devstral 2 | | `mistral/magistral-small` | text | 128,000 | 40,000 | Reasoning-enabled | After onboarding, smoke-test Medium 3.5 without starting the Gateway: ```bash openclaw infer model run --local \ --model mistral/mistral-medium-3-5 \ --prompt "Reply with exactly: mistral-ok" \ --json ``` To browse the bundled catalog row before changing config: ```bash openclaw models list --all --provider mistral --plain ``` ## Audio transcription (Voxtral) Use Voxtral for batch audio transcription through the media understanding pipeline. ```json5 { tools: { media: { audio: { enabled: true, models: [{ provider: "mistral", model: "voxtral-mini-latest" }], }, }, }, } ``` The media transcription path uses `/v1/audio/transcriptions`. The default audio model for Mistral is `voxtral-mini-latest`. ## Voice Call streaming STT The bundled `mistral` plugin registers Voxtral Realtime as a Voice Call streaming STT provider. | Setting | Config path | Default | | ------------ | ---------------------------------------------------------------------- | --------------------------------------- | | API key | `plugins.entries.voice-call.config.streaming.providers.mistral.apiKey` | Falls back to `MISTRAL_API_KEY` | | Model | `...mistral.model` | `voxtral-mini-transcribe-realtime-2602` | | Encoding | `...mistral.encoding` | `pcm_mulaw` | | Sample rate | `...mistral.sampleRate` | `8000` | | Target delay | `...mistral.targetStreamingDelayMs` | `800` | ```json5 { plugins: { entries: { "voice-call": { config: { streaming: { enabled: true, provider: "mistral", providers: { mistral: { apiKey: "${MISTRAL_API_KEY}", targetStreamingDelayMs: 800, }, }, }, }, }, }, }, } ``` OpenClaw defaults Mistral realtime STT to `pcm_mulaw` at 8 kHz so Voice Call can forward Twilio media frames directly. Use `encoding: "pcm_s16le"` and a matching `sampleRate` only if your upstream stream is already raw PCM. ## Advanced configuration `mistral/mistral-small-latest` (Mistral Small 4) and `mistral/mistral-medium-3-5` support [adjustable reasoning](https://docs.mistral.ai/studio-api/conversations/reasoning/adjustable) on the Chat Completions API via `reasoning_effort` (`none` minimizes extra thinking in the output; `high` surfaces full thinking traces before the final answer). Mistral recommends `reasoning_effort="high"` for Medium 3.5 agentic and code use cases. OpenClaw maps the session **thinking** level to Mistral's API: | OpenClaw thinking level | Mistral `reasoning_effort` | | ------------------------------------------------ | -------------------------- | | **off** / **minimal** | `none` | | **low** / **medium** / **high** / **xhigh** / **adaptive** / **max** | `high` | Do not combine Medium 3.5 reasoning mode with `temperature: 0`. The Mistral HTTP API rejects `reasoning_effort="high"` plus `temperature: 0` with a 400 response. Leave temperature unset so Mistral uses its default, or follow the [Medium 3.5 recommended settings](https://huggingface.co/mistralai/Mistral-Medium-3.5-128B) and use `temperature: 0.7` for high reasoning. For deterministic direct answers, turn thinking off/minimal so OpenClaw sends `reasoning_effort: "none"` before you lower temperature. Example model-scoped config for Medium 3.5 reasoning: ```json5 { agents: { defaults: { model: { primary: "mistral/mistral-medium-3-5" }, models: { "mistral/mistral-medium-3-5": { params: { thinking: "high" }, }, }, }, }, } ``` Other bundled Mistral catalog models do not use this parameter. Keep using `magistral-*` models when you want Mistral's native reasoning-first behavior. Mistral can serve memory embeddings via `/v1/embeddings` (default model: `mistral-embed`). ```json5 { memorySearch: { provider: "mistral" }, } ``` - Mistral auth uses `MISTRAL_API_KEY` (Bearer header). - Provider base URL defaults to `https://api.mistral.ai/v1` and accepts the standard OpenAI-compatible chat-completions request shape. - Onboarding default model is `mistral/mistral-large-latest`. - Override the base URL under `models.providers.mistral.baseUrl` only when Mistral explicitly publishes a regional endpoint you need. ## Related Choosing providers, model refs, and failover behavior. Audio transcription setup and provider selection.