Best AI for math: 403 models ranked by blind votes
Prompts that pose a math problem to work through. 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
- 403
- Level with the leader
- 24
- On our price list
- 1
- Published
- 20 October 2026
Level: the votes cannot separate it from the leader.
On LMArena’s Math board, Gemini 4 Argon (High) from Google leads with 1529 points from 273 blind votes, published 20 October 2026. 23 other models are statistically level with it. None of the models it ranks has an API price on our list yet.
Best AI for math
Prompts that pose a math problem to work through.
| # | Model | Score | Votes | Per 1M tokens, in / out |
|---|---|---|---|---|
| 1 | Gemini 4 Argon (High)Google | 95% interval 1494 to 1563 | 273 | · |
| 1 | Claude Fable 5.1 (Max)Anthropic | 95% interval 1506 to 1549 | 746 | · |
| 1 | Gemini 3.8 Flash (High)Google | 95% interval 1513 to 1540 | 2,094 | · |
| 1 | Claude Fable 5 (High)Anthropic | 95% interval 1508 to 1534 | 2,161 | · |
| 1 | Claude Opus 5 (High)Anthropic | 95% interval 1510 to 1532 | 3,315 | · |
| 1 | Claude Opus 5 (Max)Anthropic | 95% interval 1503 to 1533 | 1,597 | · |
| 1 | Claude Opus 4.6 (High)Anthropic | 95% interval 1507 to 1526 | 4,248 | · |
| 1 | Claude Opus 5.5 (High)Anthropic | 95% interval 1486 to 1538 | 491 | · |
| 1 | GPT-6.1 Sol (Max)OpenAI | 95% interval 1484 to 1540 | 390 | · |
| 1 | Gemini 3.7 Flash (High)Google | 95% interval 1491 to 1522 | 1,501 | · |
| 1 | Gemini 3.6 Flash (High)Google | 95% interval 1490 to 1519 | 1,760 | · |
| 1 | Muse Spark 1.3 (Max)Meta | 95% interval 1485 to 1523 | 948 | · |
| 1 | GLM-5.3-FlashZ.ai · open weights | 95% interval 1490 to 1518 | 1,820 | · |
| 1 | Claude Opus 4.6Anthropic | 95% interval 1495 to 1513 | 4,741 | · |
| 1 | Claude Opus 4.7 (High)Anthropic | 95% interval 1493 to 1514 | 3,293 | · |
| 1 | Claude Sonnet 5.5 (xHigh)Anthropic | 95% interval 1472 to 1529 | 416 | · |
| 1 | Kimi K3 (Max)Moonshot AI · open weights | 95% interval 1485 to 1515 | 1,535 | · |
| 1 | Qwen3.8-MaxAlibaba | 95% interval 1483 to 1514 | 1,481 | · |
| 1 | Muse Wonder (Max)Meta | 95% interval 1465 to 1532 | 277 | · |
| 1 | GLM-5.3 (Max)Z.ai · open weights | 95% interval 1480 to 1516 | 1,023 | · |
| 1 | DeepSeek-V4.1-Flash-20260910 (Max)DeepSeek · open weights | 95% interval 1473 to 1516 | 704 | · |
| 1 | Muse Spark 1.2 (xHigh)Meta | 95% interval 1465 to 1518 | 484 | · |
| 1 | MiMo-V2.6-ProXiaomi · open weights | 95% interval 1449 to 1529 | 215 | · |
| 1 | Qwen3.7-Max-PreviewAlibaba | 95% interval 1446 to 1522 | 233 | · |
| 2 | GPT-5.5OpenAI | 95% interval 1490 to 1511 | 3,518 | · |
| 2 | Gemini 3.5 Flash (High)Google | 95% interval 1485 to 1510 | 2,388 | · |
| 3 | GPT-5.6 Sol (xHigh)OpenAI | 95% interval 1482 to 1509 | 1,981 | · |
| 3 | GPT-6 Astra (Max)OpenAI | 95% interval 1465 to 1509 | 687 | · |
| 4 | Muse Spark 1.1Meta | 95% interval 1481 to 1507 | 2,076 | · |
| 6 | Claude Opus 4.8 (High)Anthropic | 95% interval 1483 to 1505 | 2,974 | · |
| 6 | GPT-5.5 (High)OpenAI | 95% interval 1483 to 1504 | 3,475 | · |
| 6 | Hy3Tencent · open weights | 95% interval 1459 to 1503 | 689 | · |
| 6 | Qwen3.6-Max-PreviewAlibaba | 95% interval 1446 to 1505 | 378 | · |
| 7 | Claude Opus 4.7Anthropic | 95% interval 1481 to 1502 | 3,389 | · |
| 7 | GPT-5.4 (High)OpenAI | 95% interval 1481 to 1502 | 3,377 | · |
| 7 | Gemini 3.1 Pro PreviewGoogle | 95% interval 1481 to 1497 | 6,734 | · |
| 7 | GLM-5.2 (Max)Z.ai · open weights | 95% interval 1474 to 1499 | 2,303 | · |
| 7 | Gemini 3.5 Flash (Medium)Google | 95% interval 1469 to 1495 | 2,214 | · |
| 9 | GPT-5.6 Terra (xHigh)OpenAI | 95% interval 1468 to 1494 | 2,056 | · |
| 10 | Kimi K2.6Moonshot AI · open weights | 95% interval 1466 to 1492 | 2,072 | · |
| 10 | GPT-5.6 Luna (xHigh)OpenAI | 95% interval 1465 to 1492 | 1,926 | · |
| 11 | ERNIE 5.1Baidu | 95% interval 1464 to 1491 | 1,981 | · |
| 11 | InklingThinky · open weights | 95% interval 1464 to 1491 | 1,951 | · |
| 14 | MiMo-V2.5-ProXiaomi · open weights | 95% interval 1469 to 1490 | 3,709 | · |
| 14 | Gemini 3 ProGoogle | 95% interval 1466 to 1488 | 2,770 | · |
| 14 | Claude Opus 4.8Anthropic | 95% interval 1466 to 1488 | 3,089 | · |
| 14 | Gemini 3 FlashGoogle | 95% interval 1462 to 1487 | 2,071 | · |
| 14 | Grok 4.5xAI | 95% interval 1459 to 1487 | 1,765 | · |
| 15 | GLM-5.1Z.ai · open weights | 95% interval 1464 to 1486 | 3,182 | · |
| 16 | Claude Sonnet 5 (High)Anthropic | 95% interval 1461 to 1485 | 2,325 | · |
| Further down the board: the other models on our price list | ||||
| 146 | gpt-oss-120bOpenAI · open weights | 95% interval 1367 to 1395 | 1,781 | · |
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