Model comparison
GPT-5 Nano vs Qwen2.5-Max
Qwen2.5-Max is the stronger model overall, scoring 40.1 to 33.4 on the Noometry Index.
Last verified . 16 shared benchmarks.
Summary
- They share 16 benchmarks with published results for both. GPT-5 Nano scores higher in 2 categories and Qwen2.5-Max in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen2.5-Max leads 55.6 to 39.4.
Side by side
| GPT-5 Nano | Qwen2.5-Max | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 33.4 | 40.1 |
| Released | 2025-08-07 | 2025-01-25 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.05 | — |
| Output $ / M tokens | $0.40 | — |
| Results tracked | 48 | 27 |
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Category by category
Coding Qwen2.5-Max leads
GPT-5 Nano: 33.3 (#248), Qwen2.5-Max: 41.2 (#118)
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Coding | 1351 | 1359 |
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| LiveBench Coding | — | 64.4% |
| ALE-Bench | 718.67 | — |
Agentic & Tool Use Not comparable
GPT-5 Nano: 25.6 (#99), Qwen2.5-Max: —
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
Reasoning Qwen2.5-Max leads
GPT-5 Nano: 16.4 (#291), Qwen2.5-Max: 24.6 (#144)
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Hard Prompts | 1329 | 1360 |
| Epoch Capabilities Index | 139.39 | 132.54 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| ARC-AGI-1 | 20.7% | — |
| Chess Puzzles | 27% | — |
| LiveBench Reasoning | — | 51.4% |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LiveBench Data Analysis | — | 67.9% |
| LMCA | 7.9% | — |
| ForecastBench | 59.1 | — |
| LiveBench | — | 62.3% |
Math Qwen2.5-Max leads
GPT-5 Nano: 29.1 (#221), Qwen2.5-Max: 34.3 (#162)
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Math | 1318 | 1369 |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| LiveBench Math | — | 58.4% |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GPT-5 Nano leads
GPT-5 Nano: 35.8 (#166), Qwen2.5-Max: 34.8 (#181)
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Expert | 1321 | 1337 |
| GPQA Diamond | 69.4% | — |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Confabulations | — | 21.8% |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
Multimodal Not comparable
GPT-5 Nano: 30.7 (#102), Qwen2.5-Max: —
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |
Multilingual Qwen2.5-Max leads
GPT-5 Nano: 45.5 (#167), Qwen2.5-Max: 48.3 (#140)
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Non-English | 1313 | 1352 |
| LMArena Chinese | 1355 | 1382 |
| LMArena German | 1329 | 1350 |
| LMArena Korean | 1269 | 1304 |
| LMArena Russian | 1296 | 1353 |
| LMArena Spanish | 1360 | 1377 |
| LMArena French | — | 1396 |
| LMArena Japanese | — | 1299 |
Instruction Following GPT-5 Nano leads
GPT-5 Nano: 75.2 (#72), Qwen2.5-Max: 71.5 (#147)
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Instruction Following | 1306 | 1335 |
| LiveBench Instruction Following | — | 75.3% |
| IFEval | 93.2% | — |
Long Context Qwen2.5-Max leads
GPT-5 Nano: 31.3 (#275), Qwen2.5-Max: 41.3 (#137)
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Longer Query | 1313 | 1358 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Qwen2.5-Max leads
GPT-5 Nano: 39.4 (#244), Qwen2.5-Max: 55.6 (#141)
| Benchmark | GPT-5 Nano | Qwen2.5-Max |
|---|---|---|
| LMArena Text | 1320 | 1367 |
| LMArena Creative Writing | 1250 | 1339 |
| LMArena Multi-Turn | 1311 | 1364 |
| Short-Story Creative Writing | — | 72.9% |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |
| LiveBench Language | — | 56.3% |
Frequently asked questions
Is GPT-5 Nano better than Qwen2.5-Max?
Qwen2.5-Max is the stronger model overall, scoring 40.1 to 33.4 on the Noometry Index.
Is GPT-5 Nano or Qwen2.5-Max better for coding?
Qwen2.5-Max scores higher on coding benchmarks: 41.2 versus 33.3 in the Noometry coding category.
How many benchmarks do GPT-5 Nano and Qwen2.5-Max share?
16 benchmarks have published results for both models. GPT-5 Nano has 48 scored results on Noometry and Qwen2.5-Max has 27.