# o3 vs Qwen3 Max

> o3 is the stronger model overall, scoring 47.4 to 43.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/o3-vs-qwen3-max
- Last updated: 2026-10-10
- Shared benchmarks: 31

## Summary

- They share 31 benchmarks with published results for both. o3 scores higher in 6 categories and Qwen3 Max in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3 leads 53.2 to 41.6.
- The biggest single-benchmark swing is Chess Puzzles: 38% for o3 and 4% for Qwen3 Max.
- Qwen3 Max is cheaper at $1.20 / $6 per million input/output tokens, against $2 / $8 for o3.
- Qwen3 Max accepts more context: 262K tokens versus 200K.

## Snapshot

| | o3 | Qwen3 Max |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 47.4 | 43.5 |
| Rank | 53 | 82 |
| Context | 200K | 262K |
| Input $/M | $2 | $1.20 |
| Output $/M | $8 | $6 |
| Weights | Proprietary | Proprietary |

## Coding

- o3: 47.3 (#57)
- Qwen3 Max: 42.4 (#93)

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| LMArena Coding | 1408 | 1456 |
| ALE-Bench | 933.55 | 370.45 |
| SWE-bench Verified | 62.3% | — |
| SWE-bench Verified (bash only) | 58.4% | — |
| Aider Polyglot | 81.3% | — |
| GSO | 8.8% | — |
| WeirdML | 52.4% | — |
| CadEval | 74% | — |

## Agentic & Tool Use

- o3: 34.3 (#42)
- Qwen3 Max: —

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| Berkeley Function Calling Leaderboard | 63% | — |
| GDPval | 30.8% | — |
| DeepResearch Bench | 45.2% | — |
| OSWorld | 23% | — |
| LMArena Search | 1144 | — |
| METR Time Horizons | 65.4% | — |
| Vending-Bench 2 | — | 71.56 |

## Reasoning

- o3: 32.1 (#66)
- Qwen3 Max: 22.0 (#186)

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| Kagi LLM Benchmark | 67.6% | 72.5% |
| Chess Puzzles | 38% | 4% |
| LMArena Hard Prompts | 1402 | 1448 |
| Mystery Game Puzzles | 29% | 5% |
| DTBench | 84.8% | 82.1% |
| LMCA | 39.7% | 28.3% |
| Epoch Capabilities Index | 146.88 | 142.41 |
| ARC-AGI-2 | 6.5% | — |
| SimpleBench | 53.1% | — |
| NYT Connections (extended) | — | 30.1% |
| ARC-AGI-1 | 60.8% | — |
| CritPt | 1.4% | — |
| EnigmaEval | 13.1% | — |
| ForecastBench | 62.5 | — |

## Math

- o3: 48.9 (#49)
- Qwen3 Max: 37.6 (#94)

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 33.3% | 18.9% |
| OTIS Mock AIME 2024-2025 | 84.4% | 73.3% |
| LMArena Math | 1426 | 1447 |
| MATH Level 5 | 97.8% | 97.1% |
| Omni-MATH | 71.4% | — |
| FrontierMath (Feb 2025 set) | 18.7% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- o3: 54.5 (#47)
- Qwen3 Max: 48.1 (#72)

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| GPQA Diamond | 81.8% | 72.6% |
| SimpleQA Verified | 49.4% | 48.7% |
| LMArena Expert | 1403 | 1457 |
| Humanity's Last Exam | 20.3% | — |
| MMLU-Pro | 85.9% | — |
| Confabulations | 14.4% | — |
| GPQA (HELM) | 75.3% | — |

## Multimodal

- o3: 40.7 (#35)
- Qwen3 Max: —

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| LMArena Vision | 1214 | — |
| GeoBench | 74% | — |
| VPCT | 52% | — |

## Multilingual

- o3: 51.9 (#99)
- Qwen3 Max: 53.9 (#58)

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| LMArena Non-English | 1402 | 1429 |
| LMArena Chinese | 1438 | 1479 |
| LMArena French | 1430 | 1450 |
| LMArena German | 1420 | 1463 |
| LMArena Japanese | 1404 | 1399 |
| LMArena Korean | 1371 | 1397 |
| LMArena Russian | 1407 | 1428 |
| LMArena Spanish | 1395 | 1463 |

## Instruction Following

- o3: 73.0 (#122)
- Qwen3 Max: 75.0 (#81)

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| LMArena Instruction Following | 1368 | 1420 |
| IFEval | 86.9% | — |

## Long Context

- o3: 53.2 (#6)
- Qwen3 Max: 41.6 (#129)

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| Fiction.LiveBench | 88.9% | 66.7% |
| CL-bench | 17.8% | 14.5% |
| LMArena Longer Query | 1372 | 1439 |

## Writing & Preference

- o3: 63.7 (#62)
- Qwen3 Max: 62.6 (#72)

| Benchmark | o3 | Qwen3 Max |
|---|---|---|
| LMArena Text | 1410 | 1439 |
| LMArena Creative Writing | 1359 | 1401 |
| LMArena Multi-Turn | 1405 | 1446 |
| Short-Story Creative Writing | 83.9% | — |
| EQ-Bench Creative Writing | 1676 | — |
| WildBench | 86.1% | — |

## FAQ

### Is o3 better than Qwen3 Max?

o3 is the stronger model overall, scoring 47.4 to 43.5 on the Noometry Index.

### Which is cheaper, o3 or Qwen3 Max?

Qwen3 Max is cheaper. It lists at $1.20 per million input tokens and $6 per million output tokens; o3 lists at $2 and $8.

### Is o3 or Qwen3 Max better for coding?

o3 scores higher on coding benchmarks: 47.3 versus 42.4 in the Noometry coding category.

### Which has the bigger context window?

Qwen3 Max does, with 262K tokens against 200K.

### How many benchmarks do o3 and Qwen3 Max share?

31 benchmarks have published results for both models. o3 has 63 scored results on Noometry and Qwen3 Max has 33.