Model comparison
gpt-oss-20b vs Qwen3-Coder 480B-A35B Instruct
Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 38.1 to 32.5 on the Noometry Index. gpt-oss-20b costs 83× 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 . 20 shared benchmarks.
Alibaba (Qwen)Summary
- They share 20 benchmarks with published results for both. gpt-oss-20b scores higher in 2 categories and Qwen3-Coder 480B-A35B Instruct in 7 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3-Coder 480B-A35B Instruct leads 55.3 to 35.5.
- The biggest single-benchmark swing is Terminal-Bench: 3.4% for gpt-oss-20b and 27.2% for Qwen3-Coder 480B-A35B Instruct.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
- Qwen3-Coder 480B-A35B Instruct accepts more context: 262K tokens versus 131K.
Side by side
| gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 32.5 | 38.1 |
| Released | 2025-08-05 | 2025-04 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 16K | 66K |
| Input $ / M tokens | $0.018 | $1.50 |
| Output $ / M tokens | $0.09 | $7.50 |
| Results tracked | 34 | 25 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding gpt-oss-20b leads
gpt-oss-20b: 37.6 (#192), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| WeirdML | 40.9% | 41.2% |
| LMArena Coding | 1306 | 1412 |
| ALE-Bench | 566.05 | 461.45 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| SciCode | 34.4% | — |
| GSO | — | 4.9% |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Qwen3-Coder 480B-A35B Instruct leads
gpt-oss-20b: 9.3 (#154), Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | 3.4% | 27.2% |
Reasoning Qwen3-Coder 480B-A35B Instruct leads
gpt-oss-20b: 19.3 (#261), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 53.2% | 49.5% |
| LMArena Hard Prompts | 1274 | 1372 |
| CritPt | 1.4% | — |
| Chess Puzzles | 4% | — |
| DTBench | 68% | — |
| LMCA | 14.5% | — |
| Epoch Capabilities Index | 137.82 | — |
Math gpt-oss-20b leads
gpt-oss-20b: 39.4 (#103), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1317 | 1365 |
| OTIS Mock AIME 2024-2025 | 65.3% | — |
| Omni-MATH | 56.5% | — |
Knowledge Qwen3-Coder 480B-A35B Instruct leads
gpt-oss-20b: 34.6 (#195), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1258 | 1338 |
| GPQA Diamond | 60.8% | — |
| MMLU-Pro | 74% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual Qwen3-Coder 480B-A35B Instruct leads
gpt-oss-20b: 42.2 (#197), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1268 | 1346 |
| LMArena Chinese | 1314 | 1357 |
| LMArena German | 1255 | 1325 |
| LMArena Japanese | 1244 | 1310 |
| LMArena Korean | 1236 | 1305 |
| LMArena Russian | 1278 | 1366 |
| LMArena Spanish | 1267 | 1360 |
| LMArena French | — | 1398 |
Instruction Following Qwen3-Coder 480B-A35B Instruct leads
gpt-oss-20b: 61.8 (#240), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1236 | 1355 |
| IFEval | 73.2% | — |
Long Context Qwen3-Coder 480B-A35B Instruct leads
gpt-oss-20b: 37.9 (#209), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1250 | 1378 |
Writing & Preference Qwen3-Coder 480B-A35B Instruct leads
gpt-oss-20b: 35.5 (#265), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | gpt-oss-20b | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1287 | 1357 |
| LMArena Creative Writing | 1201 | 1333 |
| LMArena Multi-Turn | 1268 | 1365 |
| EQ-Bench Creative Writing | 666 | — |
| WildBench | 73.7% | — |
Frequently asked questions
Is gpt-oss-20b better than Qwen3-Coder 480B-A35B Instruct?
Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 38.1 to 32.5 on the Noometry Index. gpt-oss-20b costs 83× 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-oss-20b or Qwen3-Coder 480B-A35B Instruct?
gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is gpt-oss-20b or Qwen3-Coder 480B-A35B Instruct better for coding?
gpt-oss-20b scores higher on coding benchmarks: 37.6 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Coder 480B-A35B Instruct does, with 262K tokens against 131K.
How many benchmarks do gpt-oss-20b and Qwen3-Coder 480B-A35B Instruct share?
20 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.