o1-minivsQwen3.8-27B
o1-mini | Qwen3.8-27B | |
|---|---|---|
| Specifications | ||
Parameters | — | 27B |
Context window | 128k | 262k |
| Benchmarks | ||
Agentic coding SWE-Bench ProCan the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. | — | 61.7% |
Agentic coding DeepSWE 1.1Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | — | 42.2% |
Repo-level code generation NL2Repo-BenchTests whether the AI can turn a natural-language requirement into working code across an entire repository, not just produce a single function or patch. Higher is better. | — | 42.3% |
Software engineering QwenSWEBenchQwen's in-house coding benchmark for evaluating a model's ability to complete software-engineering work. Higher is better. | — | 79% |
Competitive coding LiveCodeBenchCoding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | — | 90.3% |
Agentic terminal coding Terminal-Bench 2.1Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | — | 73% |
Professional tool use JobBenchTests the AI on professional workplace tasks that require using real work tools — the kind of multi-step jobs an office worker handles. Higher is better. | — | 33.4% |
Long-horizon office work CoWorkBenchTests long-running office tasks across fields including computer science, finance, law, medicine, and other productivity work. Higher is better. | — | 70.7% |
Multidisciplinary reasoning Humanity's Last Exam · no toolsHumanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | — | 30.8% |
Science GPQA DiamondGraduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 60% | 89.2%Best |
Instruction following IFBenchTests whether the AI can follow detailed instructions and satisfy multiple constraints at once. Higher is better. | — | 79.5% |
Agentic computer use Agent's Last Exam · pass@1A hard set of desktop and operating-system tasks an AI agent has to finish by looking at the screen and working the machine itself. The score is the share it passes outright — partial credit does not count. Higher is better. | — | 20.4% |
Agentic computer use Agent's Last Exam · scoreThe graded score on the same desktop and operating-system tasks in Agent's Last Exam, giving partial credit for progress beyond the strict pass-or-fail result. Higher is better. | — | 42.9% |
| Overview | ||
| Company | OpenAI | Qwen |
| Release date | Sep 12 2024 | Aug 14 2026 |
| Access | Proprietary | Open Weight |
Which is better: o1-mini or Qwen3.8-27B?
Qwen3.8-27B leads o1-mini on 1 of the 1 benchmark they both report (GPQA Diamond). o1-mini shipped 701 days before Qwen3.8-27B, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (o1-mini) vs 262k (Qwen3.8-27B). o1-mini is proprietary, while Qwen3.8-27B is open weight.
On GPQA Diamond, Qwen3.8-27B leads at 89.2% vs o1-mini at 60%.
Frequently asked questions
o1-mini was released by OpenAI on Sep 12 2024.
Qwen3.8-27B was released by Qwen on Aug 14 2026.
Qwen3.8-27B leads on GPQA Diamond — o1-mini 60% vs Qwen3.8-27B 89.2%.
o1-mini has a 128k context window; Qwen3.8-27B has 262k.
o1-mini is a proprietary model released by OpenAI. Qwen3.8-27B is an open weight model released by Qwen.
Other comparisons
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