Model comparison
GPT-4.1 nano vs Qwen3.6 Flash
Qwen3.6 Flash is the stronger model overall, scoring 38.8 to 27.9 on the Noometry Index. GPT-4.1 nano costs 2.4× less per token, which makes it the better buy when Qwen3.6 Flash's lead doesn't matter for your workload.
Last verified . 7 shared benchmarks.
Alibaba (Qwen)Summary
- They share 7 benchmarks with published results for both. GPT-4.1 nano scores higher in 0 categories and Qwen3.6 Flash in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.6 Flash leads 29.0 to 8.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 28.9% for GPT-4.1 nano and 84.4% for Qwen3.6 Flash.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.19 / $1.13 for Qwen3.6 Flash.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 1M.
Side by side
| GPT-4.1 nano | Qwen3.6 Flash | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 27.9 | 38.8 |
| Released | 2025-04-14 | 2026-04-27 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1M |
| Max output | 33K | 66K |
| Input $ / M tokens | $0.10 | $0.19 |
| Output $ / M tokens | $0.40 | $1.13 |
| Results tracked | 38 | 13 |
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Category by category
Coding Not comparable
GPT-4.1 nano: 24.1 (#330), Qwen3.6 Flash: —
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| Aider Polyglot | 8.9% | — |
| SciCode | 25.9% | — |
| WeirdML | 19% | — |
| LMArena Coding | 1306 | — |
| ALE-Bench | — | 326.4 |
Agentic & Tool Use Not comparable
GPT-4.1 nano: 26.5 (#104), Qwen3.6 Flash: —
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| Berkeley Function Calling Leaderboard | 33% | — |
Reasoning Qwen3.6 Flash leads
GPT-4.1 nano: 8.5 (#349), Qwen3.6 Flash: 29.0 (#96)
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| DTBench | 52.5% | 77.1% |
| LMCA | 5.5% | 31% |
| Epoch Capabilities Index | 129.62 | 143.26 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | — | 35.2% |
| Kagi LLM Benchmark | 33.3% | — |
| ARC-AGI-1 | 0% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 20% |
| LMArena Hard Prompts | 1286 | — |
| Mystery Game Puzzles | — | 18% |
Math Qwen3.6 Flash leads
GPT-4.1 nano: 26.9 (#252), Qwen3.6 Flash: 39.0 (#117)
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 84.4% |
| FrontierMath (Feb 2025 set) | 1% | 10.3% |
| FrontierMath (Tiers 1-3) | — | 22.5% |
| Omni-MATH | 36.7% | — |
| LMArena Math | 1274 | — |
| MATH Level 5 | 70% | — |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge Qwen3.6 Flash leads
GPT-4.1 nano: 21.8 (#273), Qwen3.6 Flash: 42.1 (#100)
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| GPQA Diamond | 48.9% | 83.3% |
| SimpleQA Verified | 6% | 15.9% |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
| LMArena Expert | 1272 | — |
Multimodal Not comparable
GPT-4.1 nano: 29.2 (#113), Qwen3.6 Flash: —
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| LMArena Vision | 1063 | — |
Multilingual Not comparable
GPT-4.1 nano: 41.6 (#205), Qwen3.6 Flash: —
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| LMArena Non-English | 1260 | — |
| LMArena Chinese | 1270 | — |
| LMArena German | 1288 | — |
| LMArena Japanese | 1198 | — |
| LMArena Russian | 1261 | — |
Instruction Following Not comparable
GPT-4.1 nano: 67.8 (#193), Qwen3.6 Flash: —
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| IFEval | 84.3% | — |
| LMArena Instruction Following | 1267 | — |
Long Context Not comparable
GPT-4.1 nano: 23.7 (#296), Qwen3.6 Flash: —
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| Fiction.LiveBench | 25% | — |
| LMArena Longer Query | 1283 | — |
Writing & Preference Not comparable
GPT-4.1 nano: 40.5 (#243), Qwen3.6 Flash: —
| Benchmark | GPT-4.1 nano | Qwen3.6 Flash |
|---|---|---|
| LMArena Text | 1285 | — |
| LMArena Creative Writing | 1260 | — |
| EQ-Bench Creative Writing | 946 | — |
| WildBench | 81.2% | — |
| LMArena Multi-Turn | 1277 | — |
Frequently asked questions
Is GPT-4.1 nano better than Qwen3.6 Flash?
Qwen3.6 Flash is the stronger model overall, scoring 38.8 to 27.9 on the Noometry Index. GPT-4.1 nano costs 2.4× less per token, which makes it the better buy when Qwen3.6 Flash's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or Qwen3.6 Flash?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Qwen3.6 Flash lists at $0.19 and $1.13.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 1M.
How many benchmarks do GPT-4.1 nano and Qwen3.6 Flash share?
7 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Qwen3.6 Flash has 13.