#9 of 13
Mistral
Level since 18 Oct, rising over 30 days (Direction ▲ 6.7). Latest driver: Mistral releases Mistral Large 4.
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Strongest onRelease execution5thReception6th
Lags onCapability12thUsage and adoption11thValue11th
Score55.8■ 0.0 since 18 Oct
Strength54.5Eight pillars
Direction▲ 6.7Last 30 days
Confidence
Score over time
ScoreStrength
ScoreStrength
57 daily closes, the earlier ones reconstructed. Download CSV
The eight pillars
Each pillar 0 to 100 on fixed goalposts, with its rank among the 13 ranked labs. The tick marks the median lab; points are what the pillar adds to Strength.
Why Mistral is #9
Most of its Strength comes from Capability and Reliability. Points are contributions to the Score.
- Behind Z.ai by 2.4 points. Biggest differences: Value −3.7, Ecosystem −1.8, Capability −1.7; Direction +1.1.
- Ahead of Moonshot by 4.8 points. Biggest differences: Trust, safety and privacy +3.6, Release execution +2.5, Capability −2.2; Direction +1.4.
With every pillar weight moved up to 50% either way, it ranks 6 to 9 in 90% of recalculations; with equal weights, #8.
Since 18 Oct
Score down 0.0 (55.8 to 55.8). No pillar moved by 0.1 or more.
What was measuredAll 25 readings behind this close, with source, date and goalposts
Filled: no fresh reading, so the ranked labs' median was used. Carried: a source that keeps no history, read later.
| Indicator | Reading | Scaled | Goalposts | As of |
|---|---|---|---|---|
| Arena text rating Arena (arena.ai) text leaderboard: rating of the lab's best model with 1,000 votes or more | 1429.3 mistral-large-4 | 60 | 1250 to 1550 rating | 13 Oct |
| Benchmarks Epoch AI Benchmarking Hub: the lab's best score on each of GPQA Diamond, FrontierMath tiers 1 to 3, SWE-bench Verified and OTIS Mock AIME, each placed between fixed goalposts, averaged; runs from the last 365 days, at least 3 of the 4 | 77.5 GPQA diamond 88.1% (Mistral Large 4 (high)); FrontierMath-Tiers-1-3-v2-Private 58.6% (Mistral Large 4 (high)); OTIS Mock AIME 2024-2025 98.3% (Mistral Large 4 (high)) | 78 | already 0 to 100 | 19 Oct |
| Paid adoption Published spend and paid-use evidence, latest edition of each: Ramp AI Index (share of US businesses paying the vendor, monthly), Menlo Ventures (enterprise API spend share), a16z CIO survey (share of LLM wallet), ICONIQ (share of AI builders using the provider), each placed on its own scale and averaged by weight; facts and sources at /data/adoption.json | 2.3 Ramp AI Index (2026-08): 0.2%; a16z enterprise CIO survey (2026-01): not named, below its threshold; ICONIQ, State of AI 2026: The Builder's Economy (2026-07): 8% | 2 | already 0 to 100 | 19 Oct |
| Assistant users Users of the lab's assistants (chat apps and coding agents) as the lab or its parent last disclosed them, or a panel measurement (QuestMobile) where a lab discloses none; weekly figures count as monthly (a lower bound); dated by disclosure, and only disclosures from the last 12 months count; not applicable to a lab with no figure; facts and sources at /data/assistants.json | No user count disclosed in the last 12 months | 1 million to 2 billion monthly users | ||
| Web traffic Cloudflare Radar: the lab's best rank among the top 20 generative-AI services by traffic, 21 minus the rank | 0 not in the top 20 generative-AI services | 0 | 0 to 20 rank points | 19 Oct |
| API spend share OpenRouter rankings: the lab's share of all dollars spent on OpenRouter in the last 30 days, across every model (not token volume, which cheap bulk models dominate) | 0.132 0.1% of $104.4M spent on OpenRouter in 30 days (31 models) | 6 | 0% to 35% of spend | 11 Oct |
| App charts App Store top free charts in 7 countries | 0 not in the top 100 | 0 | 0 to 100 chart points | 19 Oct |
| Coding agent downloads npm and PyPI downloads of the lab's official coding agents (such as Claude Code, Codex, Gemini CLI, Qwen Code, Mistral Vibe), last 30 days; not applicable to a lab with none; standalone IDEs without public counts (such as Antigravity) are not seen | 3932883 pypi:mistral-vibe 3932883 | 65 | 10 thousand to 100 million a month | 19 Oct |
| Coding extension installs VS Code Marketplace: installs of the lab's official coding extensions; not applicable to a lab with none | No official coding extension on the VS Code Marketplace | 100 thousand to 50 million installs | ||
| SDK downloads PyPI and npm downloads of the official SDKs, last 30 days | 48503205 pypi:mistralai 16185864; npm:@mistralai/mistralai 32317341 | 67 | 100 thousand to 1 billion a month | 19 Oct |
| Open-model downloads Hugging Face downloads of the lab's models, last 30 days | 9339135 mistralai | 59 | 10 thousand to 1 billion a month | 19 Oct |
| Shipping cadence Vikshy Wire: confirmed launches and updates of materiality 2 or more, last 90 days | 7 7 confirmed launches and updates in 90 days | 48 | 0 to 30 in 90 days | 19 Oct |
| Biggest launch Vikshy Wire: the biggest launch in the last 90 days, fading with age | 4.65 | 93 | materiality 0 to 5 | 19 Oct |
| Rating per dollar Arena rating of the lab's best-value model, less 30 points for each doubling of its blended list price (3 parts input to 1 part output), with prices below $0.30 per million counted as $0.30 | 1427.9 mistral-large-4: 1429 at $1.03/M blended | 44 | 1250 to 1650 points | 13 Oct |
| Cloud availability Amazon Bedrock, Google Cloud and Microsoft Foundry: whether each offers the lab's current models as a managed, pay-per-use API (the flagship or the model one step behind it counts 1, an older generation only 0.5, open-weight side lines 0), dated by availability; facts and sources at /data/distribution.json | 2.5 Amazon Bedrock: Mistral Large 3; no Medium 3.5; Google Cloud: Mistral Medium 3, Codestral 2, Small 3.1 (older generation, half); Microsoft Foundry: Mistral Medium 3.5 (preview), Large 3 | 83 | 0 to 3 platforms | 19 Oct |
| Open-weight hosts OpenRouter: distinct providers serving the lab's open-weight models; not applicable to a lab that publishes none (a closed model's reach is its cloud availability) | 5 Mistral, DeepInfra, Parasail, Venice, Cloudflare | 39 | 1 to 60 providers | 19 Oct |
| Developer interest Hugging Face likes on the lab's models | 44492 mistralai | 66 | 1 thousand to 316 thousand likes | 19 Oct |
| Hacker News Hacker News points on stories about the lab, last 30 days | 2785 5 stories; top: Mistral Large 4 (2043) | 77 | 0 to 30,000 points | 19 Oct |
| Press and analysts Vikshy Wire: press and analyst pieces on the lab's developments, last 30 days | 6 | 32 | 0 to 60 pieces | 19 Oct |
| Official API uptime The lab's own status page: 30-day uptime of the components that make up its model API, counting major outages in full and partial outages at 30%, the pages' own formula (degraded performance is not counted); labs label outages differently, so a measured cross-check sits beside it | No fresh reading: filled with the median | 98 | 99% to 100% over 30 days | |
| Measured uptime OpenRouter: the median uptime of the lab's own API endpoints, an independent cross-check of the status page, the mean of daily readings over 30 days | 99.9156 mean of 30 daily readings, 2026-09-20 to 2026-10-19 | 99 | 90% to 100% | 19 Oct |
| Independent assessments Independent assessments published by then, each put on 0 to 100: the Future of Life Institute AI Safety Index (40%), the Stanford Foundation Model Transparency Index (30%) and the SaferAI risk-management ratings (30%), averaged over those that cover the lab; a lab none covers is not independently assessed, and filled with the median like any gap | 12.1 2 of 3 assessments: FLI AI Safety Index (2026-07) 0.33; Foundation Model Transparency Index (2025-12) 18 | 12 | 0 to 100 | 19 Oct |
| Customer data commitments From the lab's own documentation: API and business data not used for training by default; a zero-data-retention option; a choice of data region | 2 zero data retention available, choice of data region | 67 | 0 to 3 commitments | 19 Oct |
| Security certifications From the lab's trust center: SOC 2 Type II, ISO/IEC 27001, ISO/IEC 42001 (AI management) covering its model API | 2 SOC 2 Type II, ISO/IEC 27001 | 67 | 0 to 3 certifications | 19 Oct |
| Security and privacy incidents Security breaches, data leaks and regulatory privacy actions (bans, fines, orders) affecting the lab's AI services or caused by its AI systems in the last 12 months, from reputable reporting and regulators, counted once per public disclosure, and half when the lab itself disclosed harm from its AI with no legal duty to; every fact, and what was not counted and why, is at /data/trust.json | 1 2026-05-12: A supply-chain attack pushed compromised Mistral SDK versions to npm and PyPI | 67 | 0 to 3 in 12 months, fewer is better | 19 Oct |
What moved Direction
The developments that count most in the last 30 days. Direction ▲ 6.7.
- +3.2Mistral releases Mistral Large 46 Oct · Frontier-class model launch
- +2.0Mistral releases trillion-parameter open-weight model Le Chonk6 Oct · Frontier-class model launch
- +0.6Mistral publishes Timestral-123M time-series model on Hugging Face14 Oct · Open-weight model
- +0.4Mistral publishes Voxtral Mini 4B Realtime Arabic on Hugging Face8 Oct · Open-weight model
- +0.4Mistral publishes LIDstral Arabic language identification model8 Oct · Open-weight model
- +0.1Mistral opens Munich hub for physics and industrial AI research28 Sep · New product or feature
All 6 developments, line by line
Points for materiality, times recency, times diminishing returns (or the setback cap).
| Development | Materiality | Points | Recency | Diminish or cap | Counts |
|---|---|---|---|---|---|
| Mistral opens Munich hub for physics and industrial AI research 28 Sep · New product or feature | 2 | 0.75 | 0.66 | 0.25 | +0.12 |
| Mistral releases Mistral Large 4 6 Oct · Frontier-class model launch | 5 | 4 | 0.79 | 1 | +3.16 |
| Mistral releases trillion-parameter open-weight model Le Chonk 6 Oct · Frontier-class model launch | 5 | 4 | 0.79 | 0.63 | +1.98 |
| Mistral publishes Voxtral Mini 4B Realtime Arabic on Hugging Face 8 Oct · Open-weight model | 3 | 1.5 | 0.82 | 0.36 | +0.44 |
| Mistral publishes LIDstral Arabic language identification model 8 Oct · Open-weight model | 3 | 1.5 | 0.82 | 0.29 | +0.36 |
| Mistral publishes Timestral-123M time-series model on Hugging Face 14 Oct · Open-weight model | 3 | 1.5 | 0.92 | 0.45 | +0.63 |
Latest from Mistral
What Mistral shipped, broke and changed lately. The full Mistral timeline, with every model it has released.
- 14 OctMistral publishes Timestral-123M time-series model on Hugging FaceModels · Open-weight model
- 8 OctMistral publishes LIDstral Arabic language identification modelModels · Open-weight model
- 8 OctMistral publishes Voxtral Mini 4B Realtime Arabic on Hugging FaceModels · Open-weight model
- 6 OctMistral releases trillion-parameter open-weight model Le ChonkModels · Frontier-class model launch
- 6 OctMistral releases Mistral Large 4Models · Frontier-class model launch · 512K context · $0.68 in / $2.09 out per 1M
- 28 SepMistral opens Munich hub for physics and industrial AI researchFeatures · New product or feature
