Best AI in French: 299 models ranked by blind votes
Prompts written in French. Ranked by LMArena’s blind votes, every score with its margin of error and, beside it, the list price of each model on our price list.
Scores from LMArena, published 20 October 2026, under CC BY 4.0. Prices from each maker’s pricing page, read on 15 October 2026.
- Models ranked
- 299
- Level with the leader
- 40
- On our price list
- 1
- Published
- 20 October 2026
Level: the votes cannot separate it from the leader.
On LMArena’s French board, Muse Wonder (Max) from Meta leads with 1535 points from 246 blind votes, published 20 October 2026. 39 other models are statistically level with it. None of the models it ranks has an API price on our list yet.
Best AI in French
Prompts written in French.
| # | Model | Score | Votes | Per 1M tokens, in / out |
|---|---|---|---|---|
| 1 | Muse Wonder (Max)Meta | 95% interval 1497 to 1574 | 246 | · |
| 1 | Claude Fable 5 (High)Anthropic | 95% interval 1507 to 1541 | 1,513 | · |
| 1 | Muse Spark 1.3 (Max)Meta | 95% interval 1496 to 1545 | 638 | · |
| 1 | Muse SparkMeta | 95% interval 1492 to 1549 | 479 | · |
| 1 | GLM-5.3 (Max)Z.ai · open weights | 95% interval 1496 to 1539 | 819 | · |
| 1 | Claude Opus 4.7 (High)Anthropic | 95% interval 1503 to 1531 | 2,296 | · |
| 1 | Muse Spark 1.2 (xHigh)Meta | 95% interval 1481 to 1548 | 352 | · |
| 1 | Claude Fable 5.1 (Max)Anthropic | 95% interval 1486 to 1540 | 551 | · |
| 1 | Muse Spark 1.1Meta | 95% interval 1496 to 1529 | 1,533 | · |
| 1 | Gemini 3.6 Flash (High)Google | 95% interval 1494 to 1531 | 1,149 | · |
| 1 | Kimi K3 (Max)Moonshot AI · open weights | 95% interval 1493 to 1528 | 1,305 | · |
| 1 | Claude Opus 4.6 (High)Anthropic | 95% interval 1496 to 1523 | 2,712 | · |
| 1 | Claude Opus 4.7Anthropic | 95% interval 1495 to 1523 | 2,378 | · |
| 1 | Claude Sonnet 5.5 (xHigh)Anthropic | 95% interval 1475 to 1541 | 321 | · |
| 1 | Claude Opus 4.8 (High)Anthropic | 95% interval 1493 to 1522 | 2,188 | · |
| 1 | Gemini 3.7 Flash (High)Google | 95% interval 1486 to 1527 | 925 | · |
| 1 | Gemini 3 ProGoogle | 95% interval 1487 to 1526 | 968 | · |
| 1 | Claude Opus 5 (High)Anthropic | 95% interval 1491 to 1521 | 2,185 | · |
| 1 | GPT-5.6 Sol (xHigh)OpenAI | 95% interval 1488 to 1523 | 1,373 | · |
| 1 | Claude Opus 4.8Anthropic | 95% interval 1492 to 1520 | 2,231 | · |
| 1 | GPT-6.1 Sol (Max)OpenAI | 95% interval 1471 to 1540 | 303 | · |
| 1 | Grok 4.20 Beta (Reasoning, 0309)xAI | 95% interval 1489 to 1517 | 2,220 | · |
| 1 | Gemini 3.1 Pro PreviewGoogle | 95% interval 1490 to 1513 | 4,283 | · |
| 1 | GLM-5.3-FlashZ.ai · open weights | 95% interval 1484 to 1519 | 1,348 | · |
| 1 | Qwen3.8-MaxAlibaba | 95% interval 1482 to 1520 | 1,045 | · |
| 1 | Gemini 3.8 Flash (High)Google | 95% interval 1483 to 1518 | 1,454 | · |
| 1 | GPT-5.5OpenAI | 95% interval 1486 to 1514 | 2,511 | · |
| 1 | GPT-5.4 (High)OpenAI | 95% interval 1486 to 1514 | 2,394 | · |
| 1 | GPT-5.5 (High)OpenAI | 95% interval 1482 to 1510 | 2,517 | · |
| 1 | Claude Opus 4.6Anthropic | 95% interval 1483 to 1509 | 2,908 | · |
| 1 | Grok 4.20 Beta 1xAI | 95% interval 1473 to 1516 | 862 | · |
| 1 | Mistral Large 4Mistral AI | 95% interval 1463 to 1526 | 395 | · |
| 1 | Gemini 3.5 Flash (High)Google | 95% interval 1477 to 1510 | 1,543 | · |
| 1 | Gemini 3 FlashGoogle | 95% interval 1471 to 1514 | 826 | · |
| 1 | GPT-5.5 InstantOpenAI | 95% interval 1472 to 1512 | 1,048 | · |
| 1 | Claude Opus 5 (Max)Anthropic | 95% interval 1471 to 1511 | 1,064 | · |
| 1 | Claude Opus 5.5 (High)Anthropic | 95% interval 1459 to 1523 | 340 | · |
| 1 | Claude Opus 4.5 (High, 32K, 20251101)Anthropic | 95% interval 1468 to 1510 | 846 | · |
| 1 | Grok 4.6 (High)xAI | 95% interval 1468 to 1509 | 936 | · |
| 1 | Grok 4.7 (xHigh)xAI | 95% interval 1458 to 1515 | 477 | · |
| 2 | Claude Opus 4.5 (20251101)Anthropic | 95% interval 1477 to 1506 | 2,025 | · |
| 2 | Grok 4.20 Multi-Agent Beta (0309)xAI | 95% interval 1477 to 1505 | 2,269 | · |
| 2 | GLM-5.2 (Max)Z.ai · open weights | 95% interval 1476 to 1506 | 1,902 | · |
| 2 | GPT-5.6 Terra (xHigh)OpenAI | 95% interval 1473 to 1507 | 1,461 | · |
| 2 | Dola Seed 2.0 ProByteDance | 95% interval 1476 to 1504 | 2,579 | · |
| 2 | Claude Sonnet 5 (High)Anthropic | 95% interval 1474 to 1505 | 1,708 | · |
| 2 | GPT-5.6 Luna (xHigh)OpenAI | 95% interval 1468 to 1503 | 1,350 | · |
| 3 | MiMo-V2.5-ProXiaomi · open weights | 95% interval 1476 to 1502 | 2,864 | · |
| 3 | DeepSeek-V4-ProDeepSeek · open weights | 95% interval 1472 to 1501 | 2,210 | · |
| 3 | GPT-5.4OpenAI | 95% interval 1471 to 1500 | 2,401 | · |
| Further down the board: the other models on our price list | ||||
| 157 | gpt-oss-120bOpenAI · open weights | 95% interval 1328 to 1384 | 461 | · |
Where the ranking comes from
The scores, intervals and ranks are LMArena’s. The prices are ours.
- Blind votes
- LMArena puts the same prompt to two anonymous models and asks the person who wrote it to pick the better answer. The votes place every model on one scale, where a gap of 100 points means the higher model wins about 64 times in 100.
- Style control
- The scores discount answer length and formatting, so a model does not climb by writing more or by adding headings and lists.
- Shared ranks
- A model’s rank is one plus the number of models whose whole 95% interval sits above its own. Models the votes cannot separate share a rank, which is why several can be first.
- Settings
- A model can appear more than once, at different reasoning settings: the line under its name gives the entry as LMArena lists it. Entries with web search switched on are a different product and carry no price.
- Prices
- The list price per million tokens from the maker’s own pricing page, read on 15 October 2026. It is a price per token, not per answer: a higher reasoning setting spends more tokens on the same question.
Source: LMArena, leaderboard dataset (revision 9041150e, published 20 October 2026), licensed under CC BY 4.0. We change no score: we add the prices and the links to our model pages.
What each of them costs to run
The price list works three everyday jobs on every model, and our own benchmark runs them on real business tasks to see which pass.
Scores published 20 October 2026