Model comparison
GPT-OSS 120B vs Qwen3.7 Max
Head-to-head evidence from 19 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-OSS 120B #116 (Supported); Qwen3.7 Max #10 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-OSS 120B and Qwen3.7 Max share 19 comparable benchmark results. 0 of 8 categories are comparable. 7 results are unique to GPT-OSS 120B; 39 to Qwen3.7 Max.
Updated July 23, 2026- Shared results
- 19
- GPT-OSS 120B only
- 7
- Qwen3.7 Max only
- 39
- Comparable categories
- 0 / 8
Benchmark data for GPT-OSS 120B and Qwen3.7 Max is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 19 shared benchmark results across 6 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.
Qwen3.7 Max has the larger context window at 1M, 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 | Qwen3.7 Max |
|---|---|---|---|
| Agentic | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.7 Max69.7 |
| Coding | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.7 Max77.9 |
| Reasoning | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.7 Max90.4 |
| Knowledge | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.7 Max64.2 |
| Math | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.7 Max97.1 |
| Multilingual | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.7 Max87.0 |
| Inst. Following | GPT-OSS 120BNot measured | MarginNo overlap | Qwen3.7 Max84.4 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-OSS 120B | Qwen3.7 Max | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-OSS 120B$0 input / $0 output | Qwen3.7 MaxNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-OSS 120B262 tok/s | Qwen3.7 MaxNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-OSS 120B0.79 s | Qwen3.7 MaxNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-OSS 120B128K | Qwen3.7 Max1M | Qwen3.7 Max lists the larger context window. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.7 Max | Result |
|---|---|---|---|
| AA Agentic IndexSource | 13.2% | 30.6% | Qwen3.7 Max leads |
| APEX-Agents-AASource | 3.1% | — | Not comparable |
| τ²-bench resultsSource | 65.8% | 94.7% | Qwen3.7 Max leads |
| GDPval-AASource | 15.0% | 38.7% | Qwen3.7 Max leads |
| GDPval-AASource | 799 | 1273 | Qwen3.7 Max leads |
| Gert LabsSource | 29.61% | 64.27% | Qwen3.7 Max leads |
| AA EnterpriseOps-GymSource | 25.5% | 45.0% | Qwen3.7 Max leads |
| AA ITBenchSource | 5.6% | 42.5% | Qwen3.7 Max leads |
| Terminal-Bench 2.0Source | — | 69.7% | Not comparable |
| QwenClawBenchSource | — | 64.3% | Not comparable |
| QwenWebBenchSource | — | 1568 | Not comparable |
| Claw-EvalSource | — | 65.2% | Not comparable |
| BFCL v4Source | — | 75.0% | Not comparable |
| MCP AtlasSource | — | 76.4% | Not comparable |
| VITA-BenchSource | — | 47.9% | Not comparable |
| HLE w/ toolsSource | — | 53.5% | Not comparable |
| ResearchClawBenchSource | — | 18.7% | Not comparable |
| AA BriefcaseSource | — | 908 | Not comparable |
| AA AutomationBenchSource | — | 25.6% | Not comparable |
| terminalBenchHardSource | — | 50.8% | Not comparable |
| aaTerminalBench21Source | — | 74.5% | Not comparable |
| AA Harvey LABSource | — | 83.4% | Not comparable |
Coding11 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.7 Max | Result |
|---|---|---|---|
| React Native EvalsSource | 71.6% | — | Not comparable |
| AA Coding IndexSource | 30.4% | 66.0% | Qwen3.7 Max leads |
| AA-SciCodeSource | 38.9% | 48.8% | Qwen3.7 Max leads |
| AA LiveCodeBenchSource | 87.8% | — | Not comparable |
| SWE-bench VerifiedSource | — | 80.4% | Not comparable |
| SWE-bench ProSource | — | 60.6% | Not comparable |
| SWE MultilingualSource | — | 78.3% | Not comparable |
| NL2RepoSource | — | 47.2% | Not comparable |
| SciCodeSource | — | 53.5% | Not comparable |
| LiveCodeBenchSource | — | 91.6% | Not comparable |
| Terminal-Bench 2.0Source | — | 69.7% | Not comparable |
Reasoning3 benchmarks
Knowledge15 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.7 Max | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.8% | 46.0% | Qwen3.7 Max leads |
| AA-GPQA DiamondSource | 78.2% | 92.3% | Qwen3.7 Max leads |
| AA-HLESource | 18.5% | 38.1% | Qwen3.7 Max leads |
| AA-Omniscience IndexSource | -50.0% | 14.1% | Qwen3.7 Max leads |
| AA-Omniscience AccuracySource | 21.5% | 30.1% | Qwen3.7 Max leads |
| AA-Omniscience Hallucination RateSource | 91.2% | 22.9% | Qwen3.7 Max leads |
| AA Openness IndexSource | 38.9% | — | Not comparable |
| AA MMLU-ProSource | 80.8% | — | Not comparable |
| GPQASource | — | 92.4% | Not comparable |
| GPQA-DSource | — | 92.4% | Not comparable |
| HLESource | — | 41.4% | Not comparable |
| MMLU-ProSource | — | 89.6% | Not comparable |
| MMLU-ReduxSource | — | 95% | Not comparable |
| SuperGPQASource | — | 73.6% | Not comparable |
| MMMLUSource | — | 90.3% | Not comparable |
Math4 benchmarks
Multilingual6 benchmarks
Multimodal1 benchmarks
| Benchmark | GPT-OSS 120B | Qwen3.7 Max | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 998 | 1293 | Qwen3.7 Max leads |
Frequently Asked Questions (3)
Can I compare GPT-OSS 120B and Qwen3.7 Max 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 Qwen3.7 Max today?
GPT-OSS 120B: $0.00 input / $0.00 output per 1M tokens Qwen3.7 Max: Pricing unavailable Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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