Model comparison
GPT-5 Nano vs Qwen3.5-Flash
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 33.5 on the Noometry Index.
Last verified . 29 shared benchmarks.
Alibaba (Qwen)Summary
- They share 29 benchmarks with published results for both. GPT-5 Nano scores higher in 1 category and Qwen3.5-Flash in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.5-Flash leads 57.9 to 39.1.
- The biggest single-benchmark swing is LMCA: 7.9% for GPT-5 Nano and 29.1% for Qwen3.5-Flash.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $0.10 / $0.40 for Qwen3.5-Flash.
- Qwen3.5-Flash accepts more context: 1M tokens versus 400K.
Side by side
| GPT-5 Nano | Qwen3.5-Flash | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 33.5 | 42.5 |
| Released | 2025-08-07 | 2026-02-23 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1M |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.05 | $0.10 |
| Output $ / M tokens | $0.40 | $0.40 |
| Results tracked | 49 | 32 |
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Category by category
Coding Too close to call
GPT-5 Nano: 33.6 (#254), Qwen3.5-Flash: 34.2 (#242)
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| LMArena Coding | 1351 | 1412 |
| ALE-Bench | 718.67 | 221.8 |
| SWE-bench Verified (bash only) | 34.8% | — |
| LMArena WebDev | — | 1244 |
| WeirdML | 38.1% | — |
Agentic & Tool Use Not comparable
GPT-5 Nano: 25.8 (#106), Qwen3.5-Flash: —
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
| Vending-Bench 2 | — | 462.69 |
Reasoning Qwen3.5-Flash leads
GPT-5 Nano: 16.3 (#306), Qwen3.5-Flash: 33.7 (#72)
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| Chess Puzzles | 27% | 21% |
| LMArena Hard Prompts | 1328 | 1403 |
| Mystery Game Puzzles | 9% | 20% |
| DTBench | 62.7% | 82.9% |
| LMCA | 7.9% | 29.1% |
| Epoch Capabilities Index | 139.38 | 143.98 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| ARC-AGI-1 | 20.7% | — |
| ForecastBench | 59.1 | — |
Math Qwen3.5-Flash leads
GPT-5 Nano: 29.4 (#241), Qwen3.5-Flash: 37.4 (#158)
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 20% | 18.2% |
| OTIS Mock AIME 2024-2025 | 81.1% | 84.4% |
| LMArena Math | 1317 | 1407 |
| FrontierMath (Feb 2025 set) | 8.3% | 6.2% |
| FrontierMath Tier 4 (v1) | 2.1% | 0% |
| FrontierMath Tier 4 | 2.4% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
Knowledge Qwen3.5-Flash leads
GPT-5 Nano: 35.9 (#178), Qwen3.5-Flash: 43.2 (#93)
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| GPQA Diamond | 69.4% | 82.3% |
| SimpleQA Verified | 11.7% | 20.3% |
| Vectara Hallucination Rate | 10.5% | 10.5% |
| LMArena Expert | 1321 | 1407 |
| MMLU-Pro | 77.8% | — |
| GPQA (HELM) | 67.9% | — |
Multimodal Not comparable
GPT-5 Nano: 31.3 (#108), Qwen3.5-Flash: —
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |
Multilingual Qwen3.5-Flash leads
GPT-5 Nano: 45.3 (#172), Qwen3.5-Flash: 50.5 (#121)
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| LMArena Non-English | 1313 | 1385 |
| LMArena Chinese | 1356 | 1446 |
| LMArena German | 1327 | 1390 |
| LMArena Japanese | 1226 | 1368 |
| LMArena Korean | 1269 | 1344 |
| LMArena Russian | 1296 | 1379 |
| LMArena Spanish | 1360 | 1400 |
| LMArena French | — | 1412 |
Instruction Following GPT-5 Nano leads
GPT-5 Nano: 75.0 (#79), Qwen3.5-Flash: 72.6 (#139)
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| LMArena Instruction Following | 1306 | 1374 |
| IFEval | 93.2% | — |
Long Context Qwen3.5-Flash leads
GPT-5 Nano: 31.3 (#281), Qwen3.5-Flash: 42.4 (#124)
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| LMArena Longer Query | 1312 | 1392 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Qwen3.5-Flash leads
GPT-5 Nano: 39.1 (#249), Qwen3.5-Flash: 57.9 (#122)
| Benchmark | GPT-5 Nano | Qwen3.5-Flash |
|---|---|---|
| LMArena Text | 1320 | 1397 |
| LMArena Creative Writing | 1249 | 1343 |
| LMArena Multi-Turn | 1311 | 1393 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |
Frequently asked questions
Is GPT-5 Nano better than Qwen3.5-Flash?
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 33.5 on the Noometry Index.
Which is cheaper, GPT-5 Nano or Qwen3.5-Flash?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Qwen3.5-Flash lists at $0.10 and $0.40.
Is GPT-5 Nano or Qwen3.5-Flash better for coding?
They score almost the same on coding (33.6 vs 34.2); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 400K.
How many benchmarks do GPT-5 Nano and Qwen3.5-Flash share?
29 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Qwen3.5-Flash has 32.