Model comparison
GPT-OSS 120B vs Qwen3.6-27B
Head-to-head evidence from 16 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-OSS 120B #116 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-OSS 120B and Qwen3.6-27B share 16 comparable benchmark results. 0 of 8 categories are comparable. 10 results are unique to GPT-OSS 120B; 38 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 16
- GPT-OSS 120B only
- 10
- Qwen3.6-27B only
- 38
- Comparable categories
- 0 / 8
Benchmark data for GPT-OSS 120B and Qwen3.6-27B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Qwen3.6-27B has the larger context window at 262K, compared with 128K for GPT-OSS 120B.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-OSS 120B | Δ | Qwen3.6-27B |
|---|---|---|---|
| Agentic | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Coding | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.6-27B77.5 |
| Knowledge | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.6-27B53.3 |
| Math | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.6-27B89.2 |
| Multimodal | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.6-27B76.7 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-OSS 120B | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-OSS 120B$0 input / $0 output | Qwen3.6-27B$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | GPT-OSS 120B262 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-OSS 120B0.79 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-OSS 120B128K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic13 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.6-27B | Result |
|---|---|---|---|
| AA Agentic IndexSource | 13.2% | 27.0% | Qwen3.6-27B leads |
| APEX-Agents-AASource | 3.1% | — | Not comparable |
| τ²-bench resultsSource | 65.8% | 94.2% | Qwen3.6-27B leads |
| GDPval-AASource | 15.0% | 32.0% | Qwen3.6-27B leads |
| GDPval-AASource | 799 | 1140 | Qwen3.6-27B leads |
| Gert LabsSource | 29.61% | 54.84% | Qwen3.6-27B leads |
| AA EnterpriseOps-GymSource | 25.5% | — | Not comparable |
| AA ITBenchSource | 5.6% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
Coding10 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.6-27B | Result |
|---|---|---|---|
| React Native EvalsSource | 71.6% | — | Not comparable |
| AA Coding IndexSource | 30.4% | 53.7% | Qwen3.6-27B leads |
| AA-SciCodeSource | 38.9% | 39.8% | Qwen3.6-27B leads |
| AA LiveCodeBenchSource | 87.8% | — | Not comparable |
| SWE-bench VerifiedSource | — | 77.2% | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
Reasoning2 benchmarks
Knowledge14 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.6-27B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.8% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 78.2% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 18.5% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -50.0% | -19.8% | Qwen3.6-27B leads |
| AA-Omniscience AccuracySource | 21.5% | 19.2% | GPT-OSS 120B leads |
| AA-Omniscience Hallucination RateSource | 91.2% | 48.3% | Qwen3.6-27B leads |
| AA Openness IndexSource | 38.9% | — | Not comparable |
| AA MMLU-ProSource | 80.8% | — | Not comparable |
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
Math6 benchmarks
Multilingual1 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.6-27B | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | 82.8% | — | Not comparable |
Multimodal17 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.6-27B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 998 | — | Not comparable |
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
| AA-MMMU-ProSource | — | 74.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 69.0% | 67.6% | GPT-OSS 120B leads |
Frequently Asked Questions (3)
Can I compare GPT-OSS 120B and Qwen3.6-27B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GPT-OSS 120B and Qwen3.6-27B today?
GPT-OSS 120B: $0.00 input / $0.00 output per 1M tokens Qwen3.6-27B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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