# Mistral AI — developer ecosystem report

> Mistral AI

- GitHub org: `mistralai`
- Category: ai
- Overall score: 60.0 / 100
- Overall rank: #69
- Last refreshed: 2026-08-19

## Pillar scores

| Pillar | Score / 100 | Rank | Weight in overall |
| --- | --- | --- | --- |
| Code & Polish | 48.0 | #502 | ~22% |
| Education | 81.0 | #86 | ~18% |
| AI readiness | 50.0 | #175 | part of Reach |
| Builder experience | 0.0 | #1 | ~12% |
| Community | 63.0 | #40 | ~16% |
| Reach | 61.0 | #151 | ~18% |
| Momentum | 32.0 | #467 | ~14% |

## Links

- GitHub: https://github.com/mistralai
- Website: https://mistral.ai
- Docs: https://docs.mistral.ai

## Public GitHub totals

| Metric | Value |
| --- | --- |
| Repos analyzed | 12 |
| Stars | 24,422 |
| Forks | 3,249 |
| Open issues | 473 |
| Contributors | — |

## Top repositories

| Repo | Stars | Language | Description |
| --- | --- | --- | --- |
| [mistral-inference](https://github.com/mistralai/mistral-inference) | 10,836 | Jupyter Notebook | Official inference library for Mistral models |
| [mistral-vibe](https://github.com/mistralai/mistral-vibe) | 4,847 | Python | Minimal CLI coding agent by Mistral |
| [mistral-finetune](https://github.com/mistralai/mistral-finetune) | 3,095 | Python | — |
| [cookbook](https://github.com/mistralai/cookbook) | 2,310 | Jupyter Notebook | — |
| [mistral-common](https://github.com/mistralai/mistral-common) | 932 | Python | Official inference library for pre-processing of Mistral models |
| [megablocks-public](https://github.com/mistralai/megablocks-public) | 867 | — | — |
| [client-python](https://github.com/mistralai/client-python) | 762 | Python | Python client library for Mistral AI platform |
| [client-js](https://github.com/mistralai/client-js) | 202 | JavaScript | JS Client library for Mistral AI platform |
| [client-ts](https://github.com/mistralai/client-ts) | 155 | TypeScript |  TS Client library for Mistral AI platform  |
| [mistral-evals](https://github.com/mistralai/mistral-evals) | 92 | Python | — |
| [platform-docs-public](https://github.com/mistralai/platform-docs-public) | 71 | MDX | — |
| [vllm-release](https://github.com/mistralai/vllm-release) | 54 | Python | A high-throughput and memory-efficient inference and serving engine for LLMs |

## Methodology

Scores are computed from public signals only (GitHub, package registries, docs sites, community platforms). Pillar definitions: https://www.smoower.com/docs.md

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HTML version: https://www.smoower.com/mistralai
Machine index: https://www.smoower.com/llms.txt · MCP server: https://www.smoower.com/mcp · REST API: https://www.smoower.com/api/v1