Model comparison
gpt-oss-120b vs Qwen3.6 Plus
Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 36.3 on the Noometry Index. gpt-oss-120b costs 16× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
Alibaba (Qwen)Summary
- They share 28 benchmarks with published results for both. gpt-oss-120b scores higher in 1 category and Qwen3.6 Plus in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.6 Plus leads 62.2 to 46.5.
- The biggest single-benchmark swing is GPQA Diamond: 75.8% for gpt-oss-120b and 88.4% for Qwen3.6 Plus.
- gpt-oss-120b is cheaper at $0.037 / $0.17 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-120b has downloadable open weights; the other is API-only.
Side by side
| gpt-oss-120b | Qwen3.6 Plus | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 36.3 | 47.5 |
| Released | 2025-08-05 | 2026-03-31 |
| Weights | Open | Proprietary |
| Context window | 131K | 1M |
| Max output | 41K | 66K |
| Input $ / M tokens | $0.037 | $0.50 |
| Output $ / M tokens | $0.17 | $3 |
| Results tracked | 48 | 37 |
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Category by category
Coding Qwen3.6 Plus leads
gpt-oss-120b: 33.5 (#256), Qwen3.6 Plus: 40.8 (#130)
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| SciCode | 36% | 40.7% |
| LMArena Coding | 1380 | 1467 |
| ALE-Bench | 575.62 | 670.15 |
| SWE-bench Verified | — | 57.9% |
| SWE-bench Verified (bash only) | 26% | — |
| Aider Polyglot | 41.8% | — |
| LMArena WebDev | — | 1461 |
| WeirdML | 48.2% | — |
| AlgoTune | 1.41 | — |
Agentic & Tool Use Not comparable
gpt-oss-120b: 12.2 (#153), Qwen3.6 Plus: —
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| Vending-Bench 2 | -21.53 | 5,115 |
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |
Reasoning Qwen3.6 Plus leads
gpt-oss-120b: 20.0 (#245), Qwen3.6 Plus: 29.3 (#93)
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| CritPt | 1.1% | 2.9% |
| Chess Puzzles | 20% | 17% |
| LMArena Hard Prompts | 1364 | 1449 |
| Mystery Game Puzzles | 2% | 12% |
| DTBench | 76.3% | 81.9% |
| LMCA | 22.1% | 33.1% |
| Epoch Capabilities Index | 139.93 | 147.65 |
| SimpleBench | 22.1% | — |
| Kagi LLM Benchmark | 58.6% | — |
| NYT Connections (extended) | — | 60.3% |
| Thematic Generalization | — | 59.5% |
| Surface Evolver Bench | 25% | — |
Math Too close to call
gpt-oss-120b: 52.5 (#50), Qwen3.6 Plus: 51.8 (#54)
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | 93.3% |
| LMArena Math | 1389 | 1450 |
| FrontierMath (Tiers 1-3) | — | 38.2% |
| Omni-MATH | 68.8% | — |
| FrontierMath (Feb 2025 set) | — | 26.2% |
| FrontierMath Tier 4 (v1) | — | 8.3% |
Knowledge Qwen3.6 Plus leads
gpt-oss-120b: 42.4 (#96), Qwen3.6 Plus: 56.1 (#45)
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| GPQA Diamond | 75.8% | 88.4% |
| LMArena Expert | 1356 | 1454 |
| SimpleQA Verified | — | 44.1% |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| Vectara Hallucination Rate | 14.2% | — |
| GPQA (HELM) | 68.4% | — |
Multilingual Qwen3.6 Plus leads
gpt-oss-120b: 48.0 (#147), Qwen3.6 Plus: 53.3 (#70)
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| LMArena Non-English | 1351 | 1424 |
| LMArena Chinese | 1385 | 1477 |
| LMArena French | 1369 | 1455 |
| LMArena German | 1353 | 1452 |
| LMArena Japanese | 1331 | 1389 |
| LMArena Korean | 1282 | 1379 |
| LMArena Russian | 1343 | 1434 |
| LMArena Spanish | 1389 | 1432 |
Instruction Following Qwen3.6 Plus leads
gpt-oss-120b: 69.3 (#173), Qwen3.6 Plus: 75.0 (#74)
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| LMArena Instruction Following | 1318 | 1425 |
| IFEval | 83.6% | — |
Long Context Qwen3.6 Plus leads
gpt-oss-120b: 31.4 (#278), Qwen3.6 Plus: 45.2 (#49)
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| LMArena Longer Query | 1319 | 1439 |
| Fiction.LiveBench | 44.4% | — |
| CL-bench | — | 20.3% |
Writing & Preference Qwen3.6 Plus leads
gpt-oss-120b: 46.5 (#217), Qwen3.6 Plus: 62.2 (#82)
| Benchmark | gpt-oss-120b | Qwen3.6 Plus |
|---|---|---|
| LMArena Text | 1365 | 1437 |
| LMArena Creative Writing | 1275 | 1404 |
| LMArena Multi-Turn | 1340 | 1438 |
| Short-Story Creative Writing | 77.1% | — |
| EQ-Bench Creative Writing | 961 | — |
| WildBench | 84.5% | — |
Frequently asked questions
Is gpt-oss-120b better than Qwen3.6 Plus?
Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 36.3 on the Noometry Index. gpt-oss-120b costs 16× 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-120b or Qwen3.6 Plus?
gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Qwen3.6 Plus lists at $0.50 and $3.
Is gpt-oss-120b or Qwen3.6 Plus better for coding?
Qwen3.6 Plus scores higher on coding benchmarks: 40.8 versus 33.5 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-120b and Qwen3.6 Plus share?
28 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Qwen3.6 Plus has 37.