# Mistral Large 3

Model id on AIHubMix: `mistral-large-3`
Create an API key: https://console.aihubmix.com/?utm_source=llms-agent&utm_medium=model-llms

> Mistral Large 3 is a MoE model with 67.5B total parameters and 41B active parameters, supporting a 256K-token context window. Trained from scratch on 3,000 NVIDIA H200 GPUs, it is one of the strongest permissively licensed open-weight models available.

Designed for advanced reasoning and long-context understanding, Mistral Large 3 delivers performance on par with the best instruction-tuned open-weight models for general-purpose tasks, while also offering image understanding capabilities. Its multilingual strengths are particularly notable for non-English/Chinese languages, making it well-suited for global applications.

Typical use cases include enterprise assistants, multilingual customer support, content generation and editing, data analysis over long documents, code assistance, and research workflows that require handling large corpora or complex instructions. With its MoE architecture, Mistral Large 3 balances strong performance with efficient inference, providing a versatile backbone for building reliable, production-grade AI systems.

> Capability flags (tool use, structured output, vision, reasoning, …) are **not published** for this model. AIHubMix lists them only after official confirmation and this id is not covered yet — their absence below means unverified, not unsupported. Everything else here comes from the live catalog. Verify with a minimal real call before relying on a capability (see https://aihubmix.com/agents.md — an HTTP 200 alone is not success).

- Developer: Mistral
- Context window: 256,000 tokens
- Input modalities: text, image
- Pricing: $0.5/M input tokens, $1.5/M output tokens

## Endpoints (base URL: https://aihubmix.com)

- `POST /v1/chat/completions` — OpenAI Chat Completions (`Authorization: Bearer $AIHUBMIX_API_KEY`)

## Example

```bash
curl -s https://aihubmix.com/v1/chat/completions \
  -H "Authorization: Bearer $AIHUBMIX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"mistral-large-3","messages":[{"role":"user","content":"Hello"}]}'
```

## Response

Without `stream`, `/v1/chat/completions` returns a standard Chat Completions object:

```json
{"id":"...","object":"chat.completion","model":"mistral-large-3","choices":[{"message":{"role":"assistant","content":"..."}}],"usage":{"prompt_tokens":12,"completion_tokens":24,"total_tokens":36}}
```

With `"stream": true` the response is `text/event-stream`: read each `data:` JSON chunk until `data: [DONE]`. The Messages and Gemini endpoints return their protocols' native response shapes (Anthropic / Google).

## Errors

Error responses carry a `tid` (trace id) — include it when contacting support. Reference: https://docs.aihubmix.com/en/FAQs/HTTP-Codes.md

- 400 — parameter error; most are passed through from the upstream provider (media: `prompt_missing`, `size_not_supported`, `n_not_within_range`, …)
- 401 — missing `Authorization` header, or the key is invalid/expired
- 403 — `insufficient_user_quota` (top up at https://console.aihubmix.com/?utm_source=llms-agent&utm_medium=model-llms), account suspended, or this key is not allowed to use this model
- 429 — rate limited; back off and retry
- 503 — no channel can serve the request (check the model id and your access), or the upstream provider is throttling; retry later

## More

- Model page: https://aihubmix.com/model/mistral-large-3
- Try in browser: https://playground.aihubmix.com/?model=mistral-large-3
- Compare with another model (human-facing, side-by-side specs and pricing): https://aihubmix.com/compare — pick this model and a peer there; published pairs are listed in https://aihubmix.com/sitemap-compare.xml, unpublished pairs 404 so do not compose the path by hand
- Full parameter schema: follow `https://aihubmix.com/model-data/index.json` — find this id and fetch its `path` (filenames are content-addressed; do not compose them by hand)
- Generate runnable code programmatically: npm `@aihubmix/codegen` — the generator behind the Playground's "Get Code" (4 protocols × 7 languages, media endpoints included); the body it builds is the exact wire body the Playground sends, so generated snippets and real requests cannot diverge. `@aihubmix/model-schema` (npm) translates the parameter schema above into codegen input
- Site index for agents: https://aihubmix.com/llms.txt · Onboarding: https://aihubmix.com/agents.md

---

Canonical version of this document: https://aihubmix.com/model/mistral-large-3/llms.txt