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