Best AI for hard prompts: 417 models ranked by blind votes
Prompts the arena’s classifier rates as hard: specific, technical and needing several steps to solve. 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
- 417
- Level with the leader
- 2
- On our price list
- 1
- Published
- 20 October 2026
Level: the votes cannot separate it from the leader.
On LMArena’s Hard prompts board, Gemini 4 Argon (High) from Google leads with 1549 points from 3,131 blind votes, published 20 October 2026. One other model is statistically level with it. None of the models it ranks has an API price on our list yet.
Best AI for hard prompts
Prompts the arena’s classifier rates as hard: specific, technical and needing several steps to solve.
| # | Model | Score | Votes | Per 1M tokens, in / out |
|---|---|---|---|---|
| 1 | Gemini 4 Argon (High)Google | 95% interval 1538 to 1560 | 3,131 | · |
| 1 | Claude Opus 5.5 (High)Anthropic | 95% interval 1525 to 1543 | 5,917 | · |
| 2 | Claude Opus 4.6 (High)Anthropic | 95% interval 1526 to 1535 | 52,600 | · |
| 2 | Claude Fable 5 (High)Anthropic | 95% interval 1524 to 1534 | 28,193 | · |
| 2 | Claude Opus 4.6Anthropic | 95% interval 1523 to 1531 | 56,652 | · |
| 2 | Claude Opus 4.7 (High)Anthropic | 95% interval 1521 to 1530 | 43,676 | · |
| 2 | Claude Fable 5.1 (Max)Anthropic | 95% interval 1516 to 1530 | 9,089 | · |
| 2 | Muse Wonder (Max)Meta | 95% interval 1512 to 1534 | 3,187 | · |
| 5 | Claude Opus 4.7Anthropic | 95% interval 1515 to 1523 | 44,373 | · |
| 5 | Gemini 3.8 Flash (High)Google | 95% interval 1512 to 1523 | 26,670 | · |
| 5 | Muse Spark 1.3 (Max)Meta | 95% interval 1510 to 1523 | 12,510 | · |
| 6 | Kimi K3 (Max)Moonshot AI · open weights | 95% interval 1511 to 1522 | 21,953 | · |
| 6 | Claude Opus 5 (Max)Anthropic | 95% interval 1510 to 1521 | 21,745 | · |
| 7 | Claude Opus 5 (High)Anthropic | 95% interval 1510 to 1519 | 45,136 | · |
| 7 | Claude Opus 4.8 (High)Anthropic | 95% interval 1508 to 1517 | 42,516 | · |
| 7 | GPT-5.6 Sol (xHigh)OpenAI | 95% interval 1506 to 1516 | 27,137 | · |
| 7 | Muse Spark 1.2 (xHigh)Meta | 95% interval 1503 to 1519 | 6,116 | · |
| 8 | Muse Spark 1.1Meta | 95% interval 1505 to 1515 | 29,563 | · |
| 8 | Claude Sonnet 5.5 (xHigh)Anthropic | 95% interval 1497 to 1515 | 5,015 | · |
| 8 | MiMo-V2.6-ProXiaomi · open weights | 95% interval 1492 to 1516 | 2,619 | · |
| 9 | Gemini 3.7 Flash (High)Google | 95% interval 1502 to 1513 | 19,036 | · |
| 9 | Muse SparkMeta | 95% interval 1499 to 1513 | 9,159 | · |
| 11 | Gemini 3.1 Pro PreviewGoogle | 95% interval 1504 to 1511 | 84,197 | · |
| 11 | GPT-6.1 Sol (Max)OpenAI | 95% interval 1493 to 1512 | 4,318 | · |
| 12 | GLM-5.3 (Max)Z.ai · open weights | 95% interval 1498 to 1510 | 15,149 | · |
| 15 | Claude Opus 4.8Anthropic | 95% interval 1500 to 1510 | 43,360 | · |
| 15 | Qwen3.8-MaxAlibaba | 95% interval 1498 to 1509 | 19,425 | · |
| 16 | Claude Sonnet 4.6Anthropic | 95% interval 1499 to 1508 | 46,227 | · |
| 16 | Gemini 3 ProGoogle | 95% interval 1498 to 1507 | 23,177 | · |
| 16 | Gemini 3.6 Flash (High)Google | 95% interval 1496 to 1506 | 24,133 | · |
| 16 | GPT-6 Astra (Max)OpenAI | 95% interval 1494 to 1508 | 8,080 | · |
| 16 | Qwen3.7-Max-PreviewAlibaba | 95% interval 1483 to 1507 | 2,683 | · |
| 17 | GPT-5.5 (High)OpenAI | 95% interval 1497 to 1506 | 45,527 | · |
| 17 | Claude Opus 4.5 (High, 32K, 20251101)Anthropic | 95% interval 1496 to 1506 | 20,308 | · |
| 17 | DeepSeek-V4.1-Flash-20260910 (Max)DeepSeek · open weights | 95% interval 1492 to 1506 | 8,655 | · |
| 18 | GLM-5.3-FlashZ.ai · open weights | 95% interval 1494 to 1505 | 22,985 | · |
| 19 | GPT-5.5OpenAI | 95% interval 1495 to 1503 | 47,276 | · |
| 20 | Claude Opus 4.5 (20251101)Anthropic | 95% interval 1494 to 1502 | 43,232 | · |
| 21 | GPT-5.4 (High)OpenAI | 95% interval 1492 to 1501 | 42,124 | · |
| 21 | GPT-5.2 Chat (20260210)OpenAI | 95% interval 1492 to 1501 | 22,862 | · |
| 21 | GLM-5.2 (Max)Z.ai · open weights | 95% interval 1492 to 1501 | 33,290 | · |
| 22 | Gemini 3.5 Flash (Medium)Google | 95% interval 1490 to 1500 | 31,491 | · |
| 22 | Gemini 3.5 Flash (High)Google | 95% interval 1490 to 1500 | 32,389 | · |
| 25 | MiMo-V2.5-ProXiaomi · open weights | 95% interval 1490 to 1498 | 50,452 | · |
| 25 | Gemini 3 FlashGoogle | 95% interval 1487 to 1498 | 17,156 | · |
| 27 | Qwen3.5-Max-PreviewAlibaba | 95% interval 1486 to 1497 | 14,540 | · |
| 27 | GPT-5.5 InstantOpenAI | 95% interval 1485 to 1497 | 18,434 | · |
| 31 | GPT-5.6 Terra (xHigh)OpenAI | 95% interval 1485 to 1495 | 29,450 | · |
| 34 | Claude Sonnet 5 (High)Anthropic | 95% interval 1485 to 1494 | 33,444 | · |
| 35 | GLM-5.1Z.ai · open weights | 95% interval 1485 to 1493 | 42,115 | · |
| Further down the board: the other models on our price list | ||||
| 209 | gpt-oss-120bOpenAI · open weights | 95% interval 1356 to 1368 | 14,687 | · |
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