Model comparison
gpt-oss-20b vs Qwen3.6 Plus
Qwen3.6 Plus is the stronger model overall, scoring 47.3 to 32.1 on the Noometry Index. gpt-oss-20b costs 31× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Last verified . 25 shared benchmarks.
Alibaba (Qwen)Summary
- They share 25 benchmarks with published results for both. gpt-oss-20b scores higher in 0 categories and Qwen3.6 Plus in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.6 Plus leads 62.4 to 35.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 65.3% for gpt-oss-20b and 93.3% for Qwen3.6 Plus.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.50 / $3 for Qwen3.6 Plus.
- Qwen3.6 Plus accepts more context: 1M tokens versus 131K.
- gpt-oss-20b has downloadable open weights; the other is API-only.
Side by side
| gpt-oss-20b | Qwen3.6 Plus | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 32.1 | 47.3 |
| Released | 2025-08-05 | 2026-03-31 |
| Weights | Open | Proprietary |
| Context window | 131K | 1M |
| Max output | 16K | 66K |
| Input $ / M tokens | $0.018 | $0.50 |
| Output $ / M tokens | $0.09 | $3 |
| Results tracked | 34 | 37 |
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Category by category
Coding Qwen3.6 Plus leads
gpt-oss-20b: 37.1 (#185), Qwen3.6 Plus: 40.6 (#125)
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| SciCode | 34.4% | 40.7% |
| LMArena Coding | 1307 | 1467 |
| ALE-Bench | 566.05 | 670.15 |
| SWE-bench Verified | — | 57.9% |
| LMArena WebDev | — | 1461 |
| WeirdML | 40.9% | — |
Agentic & Tool Use Not comparable
gpt-oss-20b: 9.2 (#146), Qwen3.6 Plus: —
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| Terminal-Bench | 3.4% | — |
| Vending-Bench 2 | — | 5,115 |
Reasoning Qwen3.6 Plus leads
gpt-oss-20b: 18.8 (#251), Qwen3.6 Plus: 28.5 (#89)
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| CritPt | 1.4% | 2.9% |
| Chess Puzzles | 4% | 17% |
| LMArena Hard Prompts | 1274 | 1449 |
| DTBench | 68% | 81.9% |
| LMCA | 14.5% | 33.1% |
| Epoch Capabilities Index | 137.81 | 147.67 |
| Kagi LLM Benchmark | 53.2% | — |
| NYT Connections (extended) | — | 60.3% |
| Thematic Generalization | — | 59.5% |
| Mystery Game Puzzles | — | 12% |
Math Qwen3.6 Plus leads
gpt-oss-20b: 37.6 (#93), Qwen3.6 Plus: 50.6 (#44)
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 65.3% | 93.3% |
| LMArena Math | 1317 | 1450 |
| FrontierMath (Tiers 1-3) | — | 38.2% |
| Omni-MATH | 56.5% | — |
| FrontierMath (Feb 2025 set) | — | 26.2% |
| FrontierMath Tier 4 (v1) | — | 8.3% |
Knowledge Qwen3.6 Plus leads
gpt-oss-20b: 34.6 (#186), Qwen3.6 Plus: 56.1 (#40)
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| GPQA Diamond | 60.8% | 88.4% |
| LMArena Expert | 1258 | 1456 |
| SimpleQA Verified | — | 44.1% |
| MMLU-Pro | 74% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual Qwen3.6 Plus leads
gpt-oss-20b: 42.4 (#192), Qwen3.6 Plus: 53.5 (#66)
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| LMArena Non-English | 1269 | 1424 |
| LMArena Chinese | 1311 | 1478 |
| LMArena German | 1249 | 1451 |
| LMArena Japanese | 1245 | 1389 |
| LMArena Korean | 1239 | 1381 |
| LMArena Russian | 1279 | 1434 |
| LMArena Spanish | 1267 | 1432 |
| LMArena French | — | 1454 |
Instruction Following Qwen3.6 Plus leads
gpt-oss-20b: 62.0 (#235), Qwen3.6 Plus: 75.2 (#70)
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| LMArena Instruction Following | 1236 | 1425 |
| IFEval | 73.2% | — |
Long Context Qwen3.6 Plus leads
gpt-oss-20b: 37.9 (#203), Qwen3.6 Plus: 45.1 (#48)
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| LMArena Longer Query | 1251 | 1440 |
| CL-bench | — | 20.3% |
Writing & Preference Qwen3.6 Plus leads
gpt-oss-20b: 35.8 (#260), Qwen3.6 Plus: 62.4 (#78)
| Benchmark | gpt-oss-20b | Qwen3.6 Plus |
|---|---|---|
| LMArena Text | 1288 | 1437 |
| LMArena Creative Writing | 1201 | 1405 |
| LMArena Multi-Turn | 1268 | 1438 |
| EQ-Bench Creative Writing | 666 | — |
| WildBench | 73.7% | — |
Frequently asked questions
Is gpt-oss-20b better than Qwen3.6 Plus?
Qwen3.6 Plus is the stronger model overall, scoring 47.3 to 32.1 on the Noometry Index. gpt-oss-20b costs 31× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Which is cheaper, gpt-oss-20b or Qwen3.6 Plus?
gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Qwen3.6 Plus lists at $0.50 and $3.
Is gpt-oss-20b or Qwen3.6 Plus better for coding?
Qwen3.6 Plus scores higher on coding benchmarks: 40.6 versus 37.1 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 Plus does, with 1M tokens against 131K.
How many benchmarks do gpt-oss-20b and Qwen3.6 Plus share?
25 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Qwen3.6 Plus has 37.