# o3-mini vs Qwen3.7 Max

> Qwen3.7 Max is the stronger model overall, scoring 51.4 to 36.7 on the Noometry Index. o3-mini costs 1.9× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/o3-mini-vs-qwen3-7-max
- Last updated: 2026-10-10
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. o3-mini scores higher in 1 category and Qwen3.7 Max in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.7 Max leads 62.3 to 27.6.
- The biggest single-benchmark swing is SimpleBench: 22.8% for o3-mini and 70.4% for Qwen3.7 Max.
- o3-mini is cheaper at $1.10 / $4.40 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- Qwen3.7 Max accepts more context: 1M tokens versus 200K.

## Snapshot

| | o3-mini | Qwen3.7 Max |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 36.7 | 51.4 |
| Rank | 205 | 35 |
| Context | 200K | 1M |
| Input $/M | $1.10 | $2.50 |
| Output $/M | $4.40 | $7.50 |
| Weights | Proprietary | Proprietary |

## Coding

- o3-mini: 41.4 (#116)
- Qwen3.7 Max: 50.2 (#43)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| SciCode | 39.8% | 48.8% |
| LMArena Coding | 1378 | 1498 |
| SWE-bench Verified | — | 77.3% |
| Aider Polyglot | 60.4% | — |
| LMArena WebDev | — | 1515 |
| GSO | 1.3% | — |
| WeirdML | 43.7% | — |
| LiveBench Coding | 82.7% | — |
| CadEval | 54% | — |
| ALE-Bench | — | 1,189 |

## Agentic & Tool Use

- o3-mini: 29.3 (#79)
- Qwen3.7 Max: 21.8 (#129)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| Cybench | 22.5% | — |
| GBAEval | — | 0.4% |

## Reasoning

- o3-mini: 16.3 (#295)
- Qwen3.7 Max: 48.4 (#36)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| SimpleBench | 22.8% | 70.4% |
| CritPt | 0.3% | 13.4% |
| Chess Puzzles | 17% | 19% |
| LMArena Hard Prompts | 1366 | 1483 |
| Mystery Game Puzzles | 7% | 32% |
| DTBench | 68.8% | 92.3% |
| LMCA | 19% | 44% |
| Epoch Capabilities Index | 140.35 | 153.74 |
| ARC-AGI-2 | 3% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 34.5% | — |
| EBR-Bench | — | 9.5% |
| LiveBench Reasoning | 89.6% | — |
| LiveBench Data Analysis | 70.6% | — |
| ForecastBench | 59.6 | — |
| LiveBench | 75.9% | — |

## Math

- o3-mini: 27.6 (#236)
- Qwen3.7 Max: 62.3 (#26)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 18.6% | 64.6% |
| FrontierMath Tier 4 | 0% | 34.1% |
| OTIS Mock AIME 2024-2025 | 76.9% | 95.6% |
| LMArena Math | 1396 | 1488 |
| ProofBench | — | 26% |
| LiveBench Math | 77.3% | — |
| MATH Level 5 | 96.5% | — |
| FrontierMath (Feb 2025 set) | 12.4% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- o3-mini: 38.3 (#135)
- Qwen3.7 Max: 61.7 (#24)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| GPQA Diamond | 77% | 90.9% |
| SimpleQA Verified | 15.3% | 55.8% |
| LMArena Expert | 1364 | 1488 |
| Confabulations | 17.9% | — |

## Multilingual

- o3-mini: 45.9 (#159)
- Qwen3.7 Max: 57.1 (#13)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1319 | 1475 |
| LMArena Chinese | 1379 | 1533 |
| LMArena Russian | 1304 | 1482 |
| LMArena French | 1333 | — |
| LMArena German | 1303 | — |
| LMArena Japanese | 1286 | — |
| LMArena Korean | 1314 | — |
| LMArena Spanish | 1321 | — |

## Instruction Following

- o3-mini: 75.3 (#67)
- Qwen3.7 Max: 76.9 (#34)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1338 | 1460 |
| LiveBench Instruction Following | 84.4% | — |

## Long Context

- o3-mini: 33.8 (#251)
- Qwen3.7 Max: 45.4 (#34)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1343 | 1484 |
| Fiction.LiveBench | 50% | — |

## Writing & Preference

- o3-mini: 50.4 (#177)
- Qwen3.7 Max: 65.2 (#52)

| Benchmark | o3-mini | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1337 | 1476 |
| LMArena Creative Writing | 1286 | 1450 |
| LMArena Multi-Turn | 1320 | 1482 |
| Short-Story Creative Writing | 61.7% | — |
| EQ-Bench 4 | — | 1110 |
| LiveBench Language | 50.7% | — |

## FAQ

### Is o3-mini better than Qwen3.7 Max?

Qwen3.7 Max is the stronger model overall, scoring 51.4 to 36.7 on the Noometry Index. o3-mini costs 1.9× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.

### Which is cheaper, o3-mini or Qwen3.7 Max?

o3-mini is cheaper. It lists at $1.10 per million input tokens and $4.40 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.

### Is o3-mini or Qwen3.7 Max better for coding?

Qwen3.7 Max scores higher on coding benchmarks: 50.2 versus 41.4 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.7 Max does, with 1M tokens against 200K.

### How many benchmarks do o3-mini and Qwen3.7 Max share?

25 benchmarks have published results for both models. o3-mini has 51 scored results on Noometry and Qwen3.7 Max has 33.