Model comparison
GPT-5.4 nano vs Qwen3.6 35B-A3B
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 37.6 on the Noometry Index.
Last verified . 11 shared benchmarks.
Summary
- They share 11 benchmarks with published results for both. GPT-5.4 nano scores higher in 2 categories and Qwen3.6 35B-A3B in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 35B-A3B leads 51.3 to 41.9.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 44.9% for GPT-5.4 nano and 20.4% for Qwen3.6 35B-A3B.
- GPT-5.4 nano is cheaper at $0.20 / $1.25 per million input/output tokens, against $0.25 / $1.49 for Qwen3.6 35B-A3B.
- GPT-5.4 nano accepts more context: 400K tokens versus 262K.
- Qwen3.6 35B-A3B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 nano | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 41.9 | 37.6 |
| Released | 2026-03-17 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.20 | $0.25 |
| Output $ / M tokens | $1.25 | $1.49 |
| Results tracked | 40 | 14 |
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Category by category
Coding GPT-5.4 nano leads
GPT-5.4 nano: 43.6 (#84), Qwen3.6 35B-A3B: 37.2 (#196)
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| SciCode | 46.9% | 35.8% |
| WeirdML | 49.2% | 34.5% |
| LMArena Coding | 1405 | — |
| ALE-Bench | 1,005 | — |
Agentic & Tool Use Not comparable
GPT-5.4 nano: —, Qwen3.6 35B-A3B: 22.1 (#134)
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | — | 23% |
Reasoning Qwen3.6 35B-A3B leads
GPT-5.4 nano: 23.7 (#173), Qwen3.6 35B-A3B: 28.0 (#109)
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| CritPt | 9.3% | 0.3% |
| Chess Puzzles | 30% | 26% |
| Mystery Game Puzzles | 9% | 22% |
| DTBench | 80.3% | 73.9% |
| LMCA | 36.9% | 29.7% |
| Epoch Capabilities Index | 145.81 | 143.93 |
| ARC-AGI-2 | 5.7% | — |
| Kagi LLM Benchmark | 39.7% | — |
| NYT Connections (extended) | — | 41.6% |
| ARC-AGI-1 | 51.5% | — |
| LMArena Hard Prompts | 1381 | — |
| Surface Evolver Bench | — | 44.4% |
| ForecastBench | 57.3 | — |
Math GPT-5.4 nano leads
GPT-5.4 nano: 40.9 (#88), Qwen3.6 35B-A3B: 38.9 (#121)
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 44.9% | 20.4% |
| OTIS Mock AIME 2024-2025 | 87.8% | 86.7% |
| FrontierMath Tier 4 | 12.2% | — |
| ProofBench | 5% | — |
| LMArena Math | 1406 | — |
| FrontierMath (Feb 2025 set) | 25.9% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge Qwen3.6 35B-A3B leads
GPT-5.4 nano: 41.9 (#103), Qwen3.6 35B-A3B: 51.3 (#68)
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | 78.5% | 84.8% |
| SimpleQA Verified | 11.7% | — |
| Vectara Hallucination Rate | 3.1% | — |
| LMArena Expert | 1396 | — |
Multimodal Not comparable
GPT-5.4 nano: 36.7 (#78), Qwen3.6 35B-A3B: —
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| LMArena Vision | 1196 | — |
Multilingual Not comparable
GPT-5.4 nano: 48.6 (#140), Qwen3.6 35B-A3B: —
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| LMArena Non-English | 1359 | — |
| LMArena Chinese | 1392 | — |
| LMArena French | 1396 | — |
| LMArena German | 1367 | — |
| LMArena Japanese | 1343 | — |
| LMArena Korean | 1320 | — |
| LMArena Russian | 1363 | — |
| LMArena Spanish | 1371 | — |
Instruction Following Not comparable
GPT-5.4 nano: 71.9 (#144), Qwen3.6 35B-A3B: —
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| LMArena Instruction Following | 1362 | — |
Long Context Not comparable
GPT-5.4 nano: 41.6 (#137), Qwen3.6 35B-A3B: —
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| LMArena Longer Query | 1366 | — |
Writing & Preference Not comparable
GPT-5.4 nano: 55.7 (#142), Qwen3.6 35B-A3B: —
| Benchmark | GPT-5.4 nano | Qwen3.6 35B-A3B |
|---|---|---|
| LMArena Text | 1372 | — |
| LMArena Creative Writing | 1314 | — |
| LMArena Multi-Turn | 1382 | — |
Frequently asked questions
Is GPT-5.4 nano better than Qwen3.6 35B-A3B?
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 37.6 on the Noometry Index.
Which is cheaper, GPT-5.4 nano or Qwen3.6 35B-A3B?
GPT-5.4 nano is cheaper. It lists at $0.20 per million input tokens and $1.25 per million output tokens; Qwen3.6 35B-A3B lists at $0.25 and $1.49.
Is GPT-5.4 nano or Qwen3.6 35B-A3B better for coding?
GPT-5.4 nano scores higher on coding benchmarks: 43.6 versus 37.2 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 nano does, with 400K tokens against 262K.
How many benchmarks do GPT-5.4 nano and Qwen3.6 35B-A3B share?
11 benchmarks have published results for both models. GPT-5.4 nano has 40 scored results on Noometry and Qwen3.6 35B-A3B has 14.