Model comparison
o3 vs Qwen3.7 Flash
o3 is the stronger model overall, scoring 47.5 to 39.9 on the Noometry Index. Qwen3.7 Flash costs 64× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Last verified . 6 shared benchmarks.
Alibaba (Qwen)Summary
- They share 6 benchmarks with published results for both. o3 scores higher in 3 categories and Qwen3.7 Flash in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where o3 leads 50.2 to 38.3.
- The biggest single-benchmark swing is Chess Puzzles: 38% for o3 and 23% for Qwen3.7 Flash.
- Qwen3.7 Flash is cheaper at $0.03 / $0.13 per million input/output tokens, against $2 / $8 for o3.
- Qwen3.7 Flash accepts more context: 1M tokens versus 200K.
Side by side
| o3 | Qwen3.7 Flash | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 47.5 | 39.9 |
| Released | 2025-04-16 | 2026-07-15 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 1M |
| Max output | 100K | 131K |
| Input $ / M tokens | $2 | $0.03 |
| Output $ / M tokens | $8 | $0.13 |
| Results tracked | 63 | 7 |
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Category by category
Coding Not comparable
o3: 46.8 (#64), Qwen3.7 Flash: —
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| SWE-bench Verified | 62.3% | — |
| SWE-bench Verified (bash only) | 58.4% | — |
| Aider Polyglot | 81.3% | — |
| GSO | 8.8% | — |
| WeirdML | 52.4% | — |
| LMArena Coding | 1408 | — |
| CadEval | 74% | — |
| ALE-Bench | 933.55 | — |
Agentic & Tool Use Not comparable
o3: 34.5 (#44), Qwen3.7 Flash: —
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| Berkeley Function Calling Leaderboard | 63% | — |
| GDPval | 30.8% | — |
| DeepResearch Bench | 45.2% | — |
| OSWorld | 23% | — |
| LMArena Search | 1144 | — |
| METR Time Horizons | 65.4% | — |
Reasoning o3 leads
o3: 32.0 (#78), Qwen3.7 Flash: 28.2 (#108)
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| Chess Puzzles | 38% | 23% |
| Mystery Game Puzzles | 29% | 15% |
| Epoch Capabilities Index | 146.86 | 144.64 |
| ARC-AGI-2 | 6.5% | — |
| SimpleBench | 53.1% | — |
| Kagi LLM Benchmark | 67.6% | — |
| NYT Connections (extended) | — | 43.8% |
| ARC-AGI-1 | 60.8% | — |
| CritPt | 1.4% | — |
| EnigmaEval | 13.1% | — |
| LMArena Hard Prompts | 1402 | — |
| DTBench | 84.8% | — |
| LMCA | 39.7% | — |
| ForecastBench | 62.5 | — |
Math o3 leads
o3: 50.2 (#58), Qwen3.7 Flash: 38.3 (#140)
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 33.3% | 19.3% |
| OTIS Mock AIME 2024-2025 | 84.4% | 86.7% |
| Omni-MATH | 71.4% | — |
| LMArena Math | 1426 | — |
| MATH Level 5 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 18.7% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge o3 leads
o3: 54.6 (#52), Qwen3.7 Flash: 48.9 (#75)
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| GPQA Diamond | 81.8% | 82.3% |
| Humanity's Last Exam | 20.3% | — |
| SimpleQA Verified | 49.4% | — |
| MMLU-Pro | 85.9% | — |
| Confabulations | 14.4% | — |
| GPQA (HELM) | 75.3% | — |
| LMArena Expert | 1402 | — |
Multimodal Not comparable
o3: 41.4 (#36), Qwen3.7 Flash: —
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| LMArena Vision | 1214 | — |
| GeoBench | 74% | — |
| VPCT | 52% | — |
Multilingual Not comparable
o3: 51.7 (#105), Qwen3.7 Flash: —
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| LMArena Non-English | 1401 | — |
| LMArena Chinese | 1437 | — |
| LMArena French | 1430 | — |
| LMArena German | 1420 | — |
| LMArena Japanese | 1403 | — |
| LMArena Korean | 1370 | — |
| LMArena Russian | 1406 | — |
| LMArena Spanish | 1395 | — |
Instruction Following Not comparable
o3: 72.8 (#127), Qwen3.7 Flash: —
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| IFEval | 86.9% | — |
| LMArena Instruction Following | 1368 | — |
Long Context Not comparable
o3: 53.3 (#6), Qwen3.7 Flash: —
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| Fiction.LiveBench | 88.9% | — |
| CL-bench | 17.8% | — |
| LMArena Longer Query | 1372 | — |
Writing & Preference Not comparable
o3: 63.5 (#64), Qwen3.7 Flash: —
| Benchmark | o3 | Qwen3.7 Flash |
|---|---|---|
| LMArena Text | 1410 | — |
| LMArena Creative Writing | 1359 | — |
| Short-Story Creative Writing | 83.9% | — |
| EQ-Bench Creative Writing | 1676 | — |
| WildBench | 86.1% | — |
| LMArena Multi-Turn | 1405 | — |
Frequently asked questions
Is o3 better than Qwen3.7 Flash?
o3 is the stronger model overall, scoring 47.5 to 39.9 on the Noometry Index. Qwen3.7 Flash costs 64× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Which is cheaper, o3 or Qwen3.7 Flash?
Qwen3.7 Flash is cheaper. It lists at $0.03 per million input tokens and $0.13 per million output tokens; o3 lists at $2 and $8.
Which has the bigger context window?
Qwen3.7 Flash does, with 1M tokens against 200K.
How many benchmarks do o3 and Qwen3.7 Flash share?
6 benchmarks have published results for both models. o3 has 63 scored results on Noometry and Qwen3.7 Flash has 7.