Model comparison
GPT-4.1 nano vs Qwen3-Coder 480B-A35B Instruct
Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 37.7 to 27.7 on the Noometry Index. GPT-4.1 nano costs 17× less per token, which makes it the better buy when Qwen3-Coder 480B-A35B Instruct's lead doesn't matter for your workload.
Last verified . 16 shared benchmarks.
Alibaba (Qwen)Summary
- They share 16 benchmarks with published results for both. GPT-4.1 nano scores higher in 1 category and Qwen3-Coder 480B-A35B Instruct in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in long context, where Qwen3-Coder 480B-A35B Instruct leads 42.0 to 23.7.
- The biggest single-benchmark swing is WeirdML: 19% for GPT-4.1 nano and 41.2% for Qwen3-Coder 480B-A35B Instruct.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 262K.
- Qwen3-Coder 480B-A35B Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 27.7 | 37.7 |
| Released | 2025-04-14 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 33K | 66K |
| Input $ / M tokens | $0.10 | $1.50 |
| Output $ / M tokens | $0.40 | $7.50 |
| Results tracked | 38 | 25 |
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Category by category
Coding Qwen3-Coder 480B-A35B Instruct leads
GPT-4.1 nano: 23.8 (#325), Qwen3-Coder 480B-A35B Instruct: 36.2 (#199)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| WeirdML | 19% | 41.2% |
| LMArena Coding | 1306 | 1413 |
| SWE-bench Verified (bash only) | — | 55.4% |
| Aider Polyglot | 8.9% | — |
| LMArena WebDev | — | 1275 |
| SciCode | 25.9% | — |
| GSO | — | 4.9% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use GPT-4.1 nano leads
GPT-4.1 nano: 26.3 (#98), Qwen3-Coder 480B-A35B Instruct: 23.7 (#116)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| Berkeley Function Calling Leaderboard | 33% | — |
Reasoning Qwen3-Coder 480B-A35B Instruct leads
GPT-4.1 nano: 8.6 (#344), Qwen3-Coder 480B-A35B Instruct: 24.7 (#141)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 33.3% | 49.5% |
| LMArena Hard Prompts | 1286 | 1372 |
| ARC-AGI-2 | 0% | — |
| ARC-AGI-1 | 0% | — |
| CritPt | 0% | — |
| DTBench | 52.5% | — |
| LMCA | 5.5% | — |
| Epoch Capabilities Index | 129.62 | — |
Math Qwen3-Coder 480B-A35B Instruct leads
GPT-4.1 nano: 25.5 (#246), Qwen3-Coder 480B-A35B Instruct: 34.9 (#151)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1274 | 1364 |
| OTIS Mock AIME 2024-2025 | 28.9% | — |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
Knowledge Qwen3-Coder 480B-A35B Instruct leads
GPT-4.1 nano: 21.8 (#268), Qwen3-Coder 480B-A35B Instruct: 36.4 (#159)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1272 | 1337 |
| GPQA Diamond | 48.9% | — |
| SimpleQA Verified | 6% | — |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Not comparable
GPT-4.1 nano: 28.6 (#108), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1063 | — |
Multilingual Qwen3-Coder 480B-A35B Instruct leads
GPT-4.1 nano: 41.8 (#200), Qwen3-Coder 480B-A35B Instruct: 47.8 (#143)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1260 | 1345 |
| LMArena Chinese | 1270 | 1356 |
| LMArena German | 1288 | 1324 |
| LMArena Japanese | 1199 | 1309 |
| LMArena Russian | 1261 | 1367 |
| LMArena French | — | 1394 |
| LMArena Korean | — | 1307 |
| LMArena Spanish | — | 1360 |
Instruction Following Qwen3-Coder 480B-A35B Instruct leads
GPT-4.1 nano: 68.0 (#188), Qwen3-Coder 480B-A35B Instruct: 71.8 (#142)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1267 | 1356 |
| IFEval | 84.3% | — |
Long Context Qwen3-Coder 480B-A35B Instruct leads
GPT-4.1 nano: 23.7 (#291), Qwen3-Coder 480B-A35B Instruct: 42.0 (#126)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1283 | 1379 |
| Fiction.LiveBench | 25% | — |
Writing & Preference Qwen3-Coder 480B-A35B Instruct leads
GPT-4.1 nano: 40.7 (#238), Qwen3-Coder 480B-A35B Instruct: 55.5 (#142)
| Benchmark | GPT-4.1 nano | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1285 | 1356 |
| LMArena Creative Writing | 1260 | 1333 |
| LMArena Multi-Turn | 1277 | 1365 |
| EQ-Bench Creative Writing | 946 | — |
| WildBench | 81.2% | — |
Frequently asked questions
Is GPT-4.1 nano better than Qwen3-Coder 480B-A35B Instruct?
Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 37.7 to 27.7 on the Noometry Index. GPT-4.1 nano costs 17× less per token, which makes it the better buy when Qwen3-Coder 480B-A35B Instruct's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or Qwen3-Coder 480B-A35B Instruct?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is GPT-4.1 nano or Qwen3-Coder 480B-A35B Instruct better for coding?
Qwen3-Coder 480B-A35B Instruct scores higher on coding benchmarks: 36.2 versus 23.8 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 262K.
How many benchmarks do GPT-4.1 nano and Qwen3-Coder 480B-A35B Instruct share?
16 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.