Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-OSS 20B
35
Winner · 0/8 categoriesQwen3.5 Flash
Coming soon
0/8 categoriesGPT-OSS 20B· Qwen3.5 Flash
Benchmark data for GPT-OSS 20B and Qwen3.5 Flash is coming soon on BenchLM.
BenchLM does not have sourced benchmark coverage for Qwen3.5 Flash yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Qwen3.5 Flash has the larger context window at 1M, compared with 128K for GPT-OSS 20B.
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | GPT-OSS 20B | Qwen3.5 Flash |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | 35% | — |
| OSWorld-Verified | 31% | — |
| Coding | ||
| HumanEval | 23% | — |
| SWE-bench Verified | 14% | — |
| LiveCodeBench | 11% | — |
| SWE-bench Pro | 18% | — |
| React Native Evals | 64.3% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 31% | — |
| OfficeQA Pro | 42% | — |
| Reasoning | ||
| MuSR | 27% | — |
| LongBench v2 | 48% | — |
| MRCRv2 | 48% | — |
| Knowledge | ||
| MMLU | 85.3% | — |
| GPQA | 30% | — |
| SuperGPQA | 28% | — |
| MMLU-Pro | 53% | — |
| HLE | 1% | — |
| FrontierScience | 34% | — |
| SimpleQA | 29% | — |
| Instruction Following | ||
| Coming soon | ||
| Multilingual | ||
| MGSM | 61% | — |
| MMLU-ProX | 59% | — |
| Mathematics | ||
| AIME 2023 | 31% | — |
| AIME 2024 | 33% | — |
| AIME 2025 | 32% | — |
| HMMT Feb 2023 | 27% | — |
| HMMT Feb 2024 | 29% | — |
| HMMT Feb 2025 | 28% | — |
| BRUMO 2025 | 30% | — |
| MATH-500 | 59% | — |
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still 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.
GPT-OSS 20B: $0.00 input / $0.00 output per 1M tokens Qwen3.5 Flash: Pricing unavailable Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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