openclaw/docs/providers/mistral.md

summary, read_when, title

summary	read_when	title
Use Mistral models and Voxtral transcription with OpenClaw	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	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 <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 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:

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:

openclaw models list --all --provider mistral --plain

Audio transcription (Voxtral)

Use Voxtral for batch audio transcription through the media understanding pipeline.

{
  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

{
  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`     |

<Warning>
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.
</Warning>

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" },
        },
      },
    },
  },
}
```

<Note>
Other bundled Mistral catalog models do not use this parameter. Keep using `magistral-*` models when you want Mistral's native reasoning-first behavior.
</Note>

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.