LLaMA 3.2vsQwen3.8-27B
LLaMA 3.2 | Qwen3.8-27B | |
|---|---|---|
| Specifications | ||
Parameters | 1B/3B | 27B |
Context window | — | 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. | — | 89.2% |
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 | Meta | Qwen |
| Release date | Sep 25 2024 | Aug 14 2026 |
| Access | Open Weight | Open Weight |
Which is better: LLaMA 3.2 or Qwen3.8-27B?
LLaMA 3.2 and Qwen3.8-27B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 3.2 shipped 688 days before Qwen3.8-27B, so benchmark comparisons should account for the intervening progress.
LLaMA 3.2 has 1B/3B parameters, while Qwen3.8-27B has 27B.
Direct benchmark comparisons are unavailable — LLaMA 3.2 and Qwen3.8-27B don't publish scores on any of the same benchmarks.
Frequently asked questions
LLaMA 3.2 was released by Meta on Sep 25 2024.
Qwen3.8-27B was released by Qwen on Aug 14 2026.
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