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Mistral AI llms.txt

Developer documentation for the Mistral AI platform: API references, product guides, and quickstarts for Le Chat, Vibe, Mistral AI Studio, and the Mistral API.

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# Mistral AI

> Developer documentation for the Mistral AI platform: API references, product guides, and quickstarts for Le Chat, Vibe, Mistral AI Studio, and the Mistral API.

Every link points to the markdown version of a page (same URL with a `.md` extension), served for LLM consumption. Fetch the page URL without the extension for the rendered HTML version.

## Admin

- [API reference](https://docs.mistral.ai/admin/admin-api/api-reference.md): Admin API endpoint reference generated from the OpenAPI specification.
- [Authentication](https://docs.mistral.ai/admin/admin-api/authentication.md): How Admin API keys work, where to create them, and how to authenticate requests.
- [Manage groups and roles](https://docs.mistral.ai/admin/admin-api/manage-groups-roles.md): Create user groups, manage membership and Workspace assignments, and list roles with the Admin API.
- [Manage users](https://docs.mistral.ai/admin/admin-api/manage-users.md): List, create, update, invite, and remove Organization users with the Admin API.
- [Manage Workspaces](https://docs.mistral.ai/admin/admin-api/manage-workspaces.md): List, create, update, and delete Workspaces and manage their members with the Admin API.
- [Overview](https://docs.mistral.ai/admin/admin-api/overview.md): Manage your Organization programmatically: users, groups, Workspaces, API keys, limits, usage, and audit logs.
- [Usage metrics](https://docs.mistral.ai/admin/admin-api/usage-metrics.md): Retrieve billing usage, spending and rate limits, le Chat activity, and Vibe Code analytics with the Admin API.
- [User provisioning](https://docs.mistral.ai/admin/admin-api/user-provisioning.md): Bulk-create or invite users, organize them into a user group, and grant them access to a Workspace with the Admin API.
- [Billing](https://docs.mistral.ai/admin/billing-usage/billing.md): Use Billing to manage how your Organization pays for Mistral services.
- [Invoices](https://docs.mistral.ai/admin/billing-usage/invoices.md): Find and download your invoices.
- [Subscriptions](https://docs.mistral.ai/admin/billing-usage/subscriptions.md): Use Subscription to review the Mistral plan, seats, included monthly usage, and pay-as-you-go settings active on your Organization.
- [Usage and limits](https://docs.mistral.ai/admin/billing-usage/usage-limits.md): Monitor Organization usage, understand limits, and decide where to adjust caps.
- [API keys](https://docs.mistral.ai/admin/identity-access/api-keys.md): API keys authenticate requests to the Mistral API and other Mistral tools.
- [Connectors](https://docs.mistral.ai/admin/identity-access/connectors.md): Manage organization app connections and Connector tool access from Admin.
- [Groups](https://docs.mistral.ai/admin/identity-access/groups.md): Group users to manage Workspace access and roles at scale.
- [Roles and permissions (RBAC)](https://docs.mistral.ai/admin/identity-access/roles-permissions.md): Predefined Organization and Workspace roles, what each one grants, and how to assign them.
- [Service accounts](https://docs.mistral.ai/admin/identity-access/service-accounts.md): Give a workload its own non-human identity in a workspace, with its own roles and its own credentials.
- [User management](https://docs.mistral.ai/admin/identity-access/user-management.md): Manage members, invitations, Organization roles, seats, Workspaces, groups, and user API keys.
- [Workload identity federation](https://docs.mistral.ai/admin/identity-access/workload-identity.md): Let a workload authenticate as a service account with short-lived tokens signed by your own cluster, instead of a stored secret.
- [Overview](https://docs.mistral.ai/admin/monitor-comply/audit-logs/overview.md): Audit logs provide a chronological record of actions performed within your Organization across Studio and Vibe.
- [Audit logs reference](https://docs.mistral.ai/admin/monitor-comply/audit-logs/reference.md): Audit log response fields, filters, actor types, target types, and event types.
- [Zero data retention](https://docs.mistral.ai/admin/monitor-comply/zero-data-retention.md): Learn what zero data retention covers, which API endpoints are eligible, and how to request it for your Organization.
- [Admin overview](https://docs.mistral.ai/admin/overview.md): The Admin Panel is the control surface for your Organization.
- [Admin](https://docs.mistral.ai/admin.md): Manage security, access controls, users, billing, and organizational settings for your Mistral Workspace.
- [Create your Organization](https://docs.mistral.ai/admin/set-up-organization/create-organization.md): Create your Mistral Organization and add your first members.
- [Enterprise Accounts](https://docs.mistral.ai/admin/set-up-organization/enterprise-accounts.md): Understand how Enterprise Accounts fit above Organizations.
- [Email domain authentication](https://docs.mistral.ai/admin/set-up-organization/sign-in-method/email-domain-authentication.md): Email domain authentication is available on Team plans and above.
- [SAML SSO](https://docs.mistral.ai/admin/set-up-organization/sign-in-method/saml-sso.md): SAML single sign-on (SSO) lets members of your Organization sign in with your corporate identity provider (IdP).
- [Verify your domain](https://docs.mistral.ai/admin/set-up-organization/verify-domain.md): Verify domain ownership with a DNS record.
- [Workspace usage and limits](https://docs.mistral.ai/admin/workspaces/usage-limits.md): Monitor Workspace consumption and set spending caps and rate limits.
- [Workspaces in Studio](https://docs.mistral.ai/admin/workspaces/workspaces-in-studio.md): Understand what Workspaces change for Studio users and what admins can configure.
- [Workspaces in Vibe](https://docs.mistral.ai/admin/workspaces/workspaces-in-vibe.md): Understand what Workspaces change for Vibe users and what admins can configure.
- [Your first Workspace](https://docs.mistral.ai/admin/workspaces/your-first-workspace.md): Understand what a Workspace is and create one inside your Organization.

## Getting Started

- [SDK Clients](https://docs.mistral.ai/getting-started/clients.md): ExplorerTabItem,
- [Platform overview](https://docs.mistral.ai/getting-started/platform-overview.md): Three products to use Mistral AI: Vibe for daily work and coding, Studio for the API and Playground, Admin for organization-level control.
- [Configure SSO and domain verification](https://docs.mistral.ai/getting-started/quickstarts/admin/configure-sso.md): Verify your domain and set up SAML SSO so team members sign in with your corporate identity provider. ~20 minutes.
- [Create your organization](https://docs.mistral.ai/getting-started/quickstarts/admin/create-organization.md): Create your organization, configure security policies, and invite your first team member in ~15 minutes.
- [Manage workspaces and API keys](https://docs.mistral.ai/getting-started/quickstarts/admin/manage-workspaces.md): Create isolated workspaces, generate API keys, and set usage limits for your team. ~10 minutes.
- [Build a workflow](https://docs.mistral.ai/getting-started/quickstarts/developer/build-a-workflow.md): Scaffold a durable AI workflow, run a worker, and trigger your first execution in ~15 minutes.
- [Build an agent with tools](https://docs.mistral.ai/getting-started/quickstarts/developer/build-an-agent.md): Create an AI agent that calls external functions and returns real-world data in ~10 minutes.
- [Send your first API request](https://docs.mistral.ai/getting-started/quickstarts/developer/first-api-request.md): Send your first request to the Mistral API and get a model response in ~5 minutes.
- [Set up RAG with document search](https://docs.mistral.ai/getting-started/quickstarts/developer/rag-document-search.md): Upload documents to a knowledge Library and query them with retrieval-augmented generation in ~10 minutes.
- [Activate Studio and generate an API key](https://docs.mistral.ai/getting-started/quickstarts/studio/activate-and-generate-api-key.md): Generate your first API key in Studio in ~5 minutes.
- [Create a reusable Prompt](https://docs.mistral.ai/getting-started/quickstarts/studio/create-reusable-prompt.md): Save a prompt template in Studio and choose whether to keep it private or share it with your workspace in ~5 minutes.
- [Create a Skill in Studio](https://docs.mistral.ai/getting-started/quickstarts/studio/create-skill.md): Package reusable instructions and files into a Skill from Studio in ~10 minutes.
- [Test a model in the API playground](https://docs.mistral.ai/getting-started/quickstarts/studio/test-model-playground.md): Send prompts, adjust parameters, and compare model outputs in the Studio playground in ~5 minutes.
- [Install the Vibe CLI and send your first prompt](https://docs.mistral.ai/getting-started/quickstarts/vibe-code/install-cli.md): Install the Vibe CLI, configure your API key, and send your first prompt from the terminal. ~5 minutes.
- [Scaffold a project with Vibe Code](https://docs.mistral.ai/getting-started/quickstarts/vibe-code/scaffold-a-project.md): Use Vibe Code to scaffold a new project from a natural-language description, reviewing every change before it's applied. ~10 minutes.
- [Analyze a dataset](https://docs.mistral.ai/getting-started/quickstarts/vibe-work/analyze-data.md): Upload a spreadsheet to Vibe Work and ask questions in plain language.
- [Create your first Skill](https://docs.mistral.ai/getting-started/quickstarts/vibe-work/create-first-skill.md): Package a reusable method into a Skill so Vibe Work applies the same procedure every time the task matches. ~10 minutes.
- [Run your first Vibe Work task](https://docs.mistral.ai/getting-started/quickstarts/vibe-work/first-task.md): Open Vibe Work, run a small multi-step task end-to-end, and review the result. ~5 minutes.

## Inference

- [Labs](https://docs.mistral.ai/inference/labs.md): Labs are experimental and fast moving models available for a limited amount of time.
- [Model lifecycle policy](https://docs.mistral.ai/inference/model-lifecycle.md): Each model on the Mistral Serverless API moves through a defined lifecycle, from initial release to retirement.
- [Inference](https://docs.mistral.ai/inference.md): Explore model serving, model choice, request behavior, and inference-related API concepts.
- [Priority Tier](https://docs.mistral.ai/inference/priority-tier.md): Priority Tier gives eligible API requests priority queueing for workloads that need more predictable access to shared infrastructure.
- [Prompting](https://docs.mistral.ai/inference/prompting.md): When you first start using Mistral models, your initial interaction will revolve around prompts.
- [Regional inference](https://docs.mistral.ai/inference/regional-inference.md): Mistral offers regional inference as an optional service through dedicated API endpoints.
- [Sampling](https://docs.mistral.ai/inference/sampling.md): Here, we will discuss the sampling settings that influence the output of Large Language Models (LLMs).
- [API pricing](https://docs.mistral.ai/inference/pricing.md): Pricing for Mistral models through the API, organized by family.
- [Model Selection Guide](https://docs.mistral.ai/inference/model-selection-guide.md): Compare current Mistral models on speed, performance, modalities, context size, pricing and license.

## Models

- [Models Overview](https://docs.mistral.ai/models.md): Every Mistral model with its API name, status and context length, including deprecated and retired models.
- [Z.ai GLM 5.3](https://docs.mistral.ai/models/zai-glm-5-3.md): A third-party open weight text model from Z.ai with a 1M-token context window.
- [Z.ai GLM 5.2](https://docs.mistral.ai/models/zai-glm-5-2.md): A third-party open weight text model from Z.ai with a 1M-token context window.
- [Shieldstral 1.0](https://docs.mistral.ai/models/shieldstral-1-0.md): Compact multimodal moderation model for text and image safety classification.
- [Timestral 1.0 209M](https://docs.mistral.ai/models/timestral-1-0-209m.md): A time series foundation model for zero-shot forecasting with covariate support and probabilistic outputs.
- [Timestral 1.0 123M](https://docs.mistral.ai/models/timestral-1-0-123m.md): A time series foundation model for zero-shot forecasting with covariate support and probabilistic outputs.
- [Timestral 1.0 28M](https://docs.mistral.ai/models/timestral-1-0-28m.md): A time series foundation model for zero-shot forecasting with covariate support and probabilistic outputs.
- [Timestral 1.0 5M](https://docs.mistral.ai/models/timestral-1-0-5m.md): A time series foundation model for zero-shot forecasting with covariate support and probabilistic outputs.
- [Mistral Medium 3.5](https://docs.mistral.ai/models/mistral-medium-3-5-26-04.md): Our frontier-class multimodal model optimized for agentic and coding use cases.
- [Voxtral TTS](https://docs.mistral.ai/models/voxtral-tts-26-03.md): State-of-the-art TTS with zero-shot voice cloning and multilingual support.
- [Voxtral Mini Transcribe 3](https://docs.mistral.ai/models/voxtral-mini-transcribe-3-0.md): Strong transcription and diarization at a competitive price point.
- [Voxtral Small Transcribe 3](https://docs.mistral.ai/models/voxtral-small-transcribe-3-0.md): Flagship transcription and diarization model with SOTA accuracy.
- [Voxtral Mini Transcribe Realtime 3](https://docs.mistral.ai/models/voxtral-mini-transcribe-realtime-3-0.md): Realtime transcription model for agentic use-cases with configurable latency and turn detection.
- [Voxtral TTS 3](https://docs.mistral.ai/models/voxtral-mini-tts-3-0.md): State-of-the-art TTS with zero-shot and professional voice cloning, 9 languages, and streaming.
- [Mistral Small 4](https://docs.mistral.ai/models/mistral-small-4-0-26-03.md): Hybrid model unifying instruct, reasoning, and coding in a single efficient model.
- [Leanstral 1.5](https://docs.mistral.ai/models/leanstral-1-5.md): Updated code agent for Lean 4 formal proof engineering and automated theorem proving.
- [Leanstral](https://docs.mistral.ai/models/leanstral-26-03.md): Open-source code agent for Lean 4 formal proof engineering.
- [Mistral Large 4](https://docs.mistral.ai/models/mistral-large-4-0.md): A state-of-the-art, open-weight, general-purpose multimodal model.
- [Mistral Large 3](https://docs.mistral.ai/models/mistral-large-3-25-12.md): A state-of-the-art, open-weight, general-purpose multimodal model.
- [Mistral Medium 3.1](https://docs.mistral.ai/models/mistral-medium-3-1-25-08.md): Our frontier-class multimodal model released August 2025.
- [Mistral Small 3.2](https://docs.mistral.ai/models/mistral-small-3-2-25-06.md): An update to our previous small model, released June 2025.
- [OCR 4.1](https://docs.mistral.ai/models/ocr-4-1.md): Our latest OCR service with paragraph-level bounding boxes, structural block labels, and block-level confidence scores.
- [OCR 4.0](https://docs.mistral.ai/models/ocr-4-0.md): Our latest OCR service with paragraph-level bounding boxes and structural block labels.
- [OCR 3](https://docs.mistral.ai/models/ocr-3-25-12.md): Our OCR service powering our Document AI stack. OCR 4 is available as the newer model. OCR 3 remains available for existing integrations and production workloads.
- [Voxtral Mini Transcribe](https://docs.mistral.ai/models/voxtral-mini-transcribe-25-07.md): An efficient audio input model, pre-trained and optimized for transcription purposes.
- [Voxtral Mini Transcribe 2](https://docs.mistral.ai/models/voxtral-mini-transcribe-26-02.md): An efficient audio input model, pre-trained and optimized for transcription purposes.
- [Voxtral Mini Transcribe Realtime](https://docs.mistral.ai/models/voxtral-mini-transcribe-realtime-26-02.md): An efficient audio input model, pre-trained and optimized for live transcription purposes.
- [Codestral](https://docs.mistral.ai/models/codestral-25-08.md): Our cutting-edge language model for code completion released end of July 2025.
- [Devstral 2](https://docs.mistral.ai/models/devstral-2-25-12.md): Our frontier code agents model for solving software engineering tasks.
- [Magistral Medium 1.1](https://docs.mistral.ai/models/magistral-medium-1-1-25-07.md): Our frontier-class reasoning model released July 2025.
- [Codestral Embed](https://docs.mistral.ai/models/codestral-embed-25-05.md): Our state-of-the-art semantic for extracting representation of code extracts
- [Mistral Small Creative](https://docs.mistral.ai/models/mistral-small-creative-25-12.md): A specialized model designed for creative writing and dynamic character interaction.
- [Devstral Small 2](https://docs.mistral.ai/models/devstral-small-2-25-12.md): Model that excels at using tools to explore codebases, editing multiple files and power software engineering agents.
- [Ministral 3 14B](https://docs.mistral.ai/models/ministral-3-14b-25-12.md): A powerful model offering best-in-class text and vision capabilities. 
- [Ministral 3 8B](https://docs.mistral.ai/models/ministral-3-8b-25-12.md): A powerful and efficient model offering best-in-class text and vision capabilities. 
- [Ministral 3 3B](https://docs.mistral.ai/models/ministral-3-3b-25-12.md): A tiny and efficient model offering best-in-class text and vision capabilities. 
- [Magistral Medium 1.2](https://docs.mistral.ai/models/magistral-medium-1-2-25-09.md): Our frontier-class multimodal reasoning model.
- [Magistral Small 1.2](https://docs.mistral.ai/models/magistral-small-1-2-25-09.md): Our small multimodal reasoning model.
- [Magistral Small 1.1](https://docs.mistral.ai/models/magistral-small-1-1-25-07.md): Our small reasoning model released July 2025.
- [Voxtral Mini](https://docs.mistral.ai/models/voxtral-mini-25-07.md): A mini version of our first audio input model.
- [Voxtral Small](https://docs.mistral.ai/models/voxtral-small-25-07.md): Our first model with audio input capabilities for instruct use cases.
- [Devstral Medium 1.0](https://docs.mistral.ai/models/devstral-medium-1-0-25-07.md): An enterprise grade text model, that excels at SWE use cases.
- [Devstral Small

Measured from the saved file

Linked document

UTF-8 text size
77.6 KB79510 bytes
Token count
18723o200k_base encoding
Markdown links
424424 distinct URLs
Fenced code blocks
0453 lines in the file

Size measures the captured UTF-8 text, not compressed transfer size. Tokens are counted with a named tokenizer; other models can count differently. Neither measure establishes context compatibility or answer quality.

Project H1
Mistral AI

Opening blockquote

Developer documentation for the Mistral AI platform: API references, product guides, and quickstarts for Le Chat, Vibe, Mistral AI Studio, and the Mistral API.

Context architecture

How the content is divided

8 H2 sections organize 424 parsed Markdown links. 422 links point to .md or .markdown paths; 0 link occurrences use another hostname. Linked destinations have not been recursively validated.

H2 sectionLinksUTF-8 bytesTokens
AdminLine 73356321262
Getting StartedLine 43183750890
InferenceLine 6491494326
ModelsLine 7676113633301
ResourcesLine 155223651854
StudioLine 180204422789392
VibeLine 38760106172532
OptionalLine 450 · Optional226662

Link counts exclude parsed fenced and inline code and resolve relative destinations against the final endpoint. Section sizes cover the text below each H2 until the next H2.

Embedded material

Code, installation and API examples

Fenced blocks
0 closed
Declared languages
No fenced blocks detected
Package-install commands
0 detected in fenced or inline code
Authentication examples
0 fenced lines match API-key, Authorization, Bearer, OAuth or access-token patterns
HTTP request examples
0 fenced lines match request-method patterns
Authentication links
1 links have authentication-related labels

Embedded example text and links to further documentation are counted separately. A code block does not establish that a sample runs or that an authentication flow succeeds.

Publisher prioritization

The Optional section

1 H2 section named “Optional” contain 2 parsed links. 422 links sit outside those sections. That puts 0.5% of the file’s parsed links under Optional.

The community proposal uses Optional by convention for secondary links that can be skipped for a shorter context. This label does not establish that everything outside it is critical, or that the material inside it is deprecated.

Machine-readable routes

MCP references and configuration text

MCP-related text was detected in the captured file. 3 links have MCP-related labels or paths. 0 fenced lines match mcpServers, mcp_servers or an mcp add command.

These are text and link observations. No MCP server connection, authentication or tool call was tested.

Index and bundle

llms-full.txt companion

Verified text companion

Text companion verified

https://docs.mistral.ai/llms-full.txt ↗
Discovery
Linked from this llms.txt
HTTP response
206 · text/plain; charset=utf-8
Text size
3.1 MB · 3272472 bytes (server-reported)
Token count
Not measured for the whole file
Retrieval scope
Bounded prefix inspected; the whole body was not downloaded

A verified text response establishes a companion at the checked URL. It does not prove the bundle contains all product documentation, that generation is automated, or that it fits an assistant’s context window.

Change evidence

What can be said about freshness

This capture establishes a baseline. Update frequency cannot be determined from one observation.

Linked release and migration material

21 links have release, changelog, deprecation or migration terms in their labels or paths. These provide places to investigate product changes separately.

File changes can reveal documentation edits or navigation changes. They do not by themselves measure product release velocity, accuracy, agent adoption or AI visibility.

Capture identity and measurement method
Requested endpoint
https://docs.mistral.ai/llms.txt
Final endpoint
https://docs.mistral.ai/llms.txt
HTTP status
200
Content type
text/plain; charset=utf-8
Text retrieval
Firecrawl literal text capture
Tokenizer
tiktoken 0.14.0 · o200k_base
SHA-256 of saved UTF-8 text
3e91645541562662fe509625292935a330a05320d661b0d34e996169214294fc

Counts use a deterministic parser, not a spec-compliance grade. Unusual Markdown and indented code can fall outside its recognized patterns. See the llms.txt proposal and tokenizer implementation.

Related tools and resources

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