Model comparison
GPT-5.4 nano vs Qwen3 32B
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 39.2 on the Noometry Index.
Last verified . 23 shared benchmarks.
Summary
- They share 23 benchmarks with published results for both. GPT-5.4 nano scores higher in 7 categories and Qwen3 32B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.4 nano leads 43.6 to 37.7.
- The biggest single-benchmark swing is Chess Puzzles: 30% for GPT-5.4 nano and 5% for Qwen3 32B.
- GPT-5.4 nano is cheaper at $0.20 / $1.25 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.
- GPT-5.4 nano accepts more context: 400K tokens versus 131K.
- Qwen3 32B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.4 nano | Qwen3 32B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 41.9 | 39.2 |
| Released | 2026-03-17 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 400K | 131K |
| Max output | 128K | 16K |
| Input $ / M tokens | $0.20 | $0.70 |
| Output $ / M tokens | $1.25 | $2.80 |
| Results tracked | 40 | 26 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.4 nano leads
GPT-5.4 nano: 43.6 (#84), Qwen3 32B: 37.7 (#190)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| SciCode | 46.9% | 35.4% |
| LMArena Coding | 1405 | 1358 |
| Aider Polyglot | — | 40% |
| WeirdML | 49.2% | — |
| ALE-Bench | 1,005 | — |
Agentic & Tool Use Not comparable
GPT-5.4 nano: —, Qwen3 32B: 32.6 (#62)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 48.7% |
Reasoning GPT-5.4 nano leads
GPT-5.4 nano: 23.7 (#173), Qwen3 32B: 20.2 (#241)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| Kagi LLM Benchmark | 39.7% | 54.9% |
| CritPt | 9.3% | 0.3% |
| Chess Puzzles | 30% | 5% |
| LMArena Hard Prompts | 1381 | 1334 |
| DTBench | 80.3% | 67.5% |
| LMCA | 36.9% | 17.3% |
| Epoch Capabilities Index | 145.81 | 138.51 |
| ARC-AGI-2 | 5.7% | — |
| ARC-AGI-1 | 51.5% | — |
| Mystery Game Puzzles | 9% | — |
| ForecastBench | 57.3 | — |
Math GPT-5.4 nano leads
GPT-5.4 nano: 40.9 (#88), Qwen3 32B: 39.7 (#99)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 87.8% | 66.9% |
| LMArena Math | 1406 | 1399 |
| FrontierMath (Tiers 1-3) | 44.9% | — |
| FrontierMath Tier 4 | 12.2% | — |
| ProofBench | 5% | — |
| FrontierMath (Feb 2025 set) | 25.9% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge GPT-5.4 nano leads
GPT-5.4 nano: 41.9 (#103), Qwen3 32B: 40.0 (#125)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| GPQA Diamond | 78.5% | 65.7% |
| Vectara Hallucination Rate | 3.1% | 5.9% |
| LMArena Expert | 1396 | 1362 |
| SimpleQA Verified | 11.7% | — |
Multimodal Not comparable
GPT-5.4 nano: 36.7 (#78), Qwen3 32B: —
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| LMArena Vision | 1196 | — |
Multilingual GPT-5.4 nano leads
GPT-5.4 nano: 48.6 (#140), Qwen3 32B: 45.6 (#167)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1359 | 1317 |
| LMArena Chinese | 1392 | 1357 |
| LMArena German | 1367 | 1341 |
| LMArena Russian | 1363 | 1311 |
| LMArena French | 1396 | — |
| LMArena Japanese | 1343 | — |
| LMArena Korean | 1320 | — |
| LMArena Spanish | 1371 | — |
Instruction Following GPT-5.4 nano leads
GPT-5.4 nano: 71.9 (#144), Qwen3 32B: 68.9 (#179)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1362 | 1305 |
Long Context Qwen3 32B leads
GPT-5.4 nano: 41.6 (#137), Qwen3 32B: 43.8 (#87)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1366 | 1327 |
| Fiction.LiveBench | — | 74.2% |
Writing & Preference GPT-5.4 nano leads
GPT-5.4 nano: 55.7 (#142), Qwen3 32B: 52.9 (#163)
| Benchmark | GPT-5.4 nano | Qwen3 32B |
|---|---|---|
| LMArena Text | 1372 | 1340 |
| LMArena Creative Writing | 1314 | 1297 |
| LMArena Multi-Turn | 1382 | 1331 |
Frequently asked questions
Is GPT-5.4 nano better than Qwen3 32B?
GPT-5.4 nano is the stronger model overall, scoring 41.9 to 39.2 on the Noometry Index.
Which is cheaper, GPT-5.4 nano or Qwen3 32B?
GPT-5.4 nano is cheaper. It lists at $0.20 per million input tokens and $1.25 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.
Is GPT-5.4 nano or Qwen3 32B better for coding?
GPT-5.4 nano scores higher on coding benchmarks: 43.6 versus 37.7 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 nano does, with 400K tokens against 131K.
How many benchmarks do GPT-5.4 nano and Qwen3 32B share?
23 benchmarks have published results for both models. GPT-5.4 nano has 40 scored results on Noometry and Qwen3 32B has 26.