Claude Sonnet 4.6vsQwen3.8-27B
Claude Sonnet 4.6 | Qwen3.8-27B | |
|---|---|---|
| Specifications | ||
Parameters | — | 27B |
Context window | — | 262k |
| Benchmarks | ||
Nonsense detection BullshitBench v2Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 91% | — |
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% |
Coding SWE-Bench VerifiedReal coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 79.6% | — |
Agentic coding CursorBench v3.1Cursor's own test of harder, real-world coding tasks inside a code editor. Higher is better. | 49% | — |
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. | 30% | 42.2%Best |
Next.js coding Next.js EvalsVercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 58% | — |
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% |
Multi-step tool use MCP AtlasCan the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better. | 69.5% | — |
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% |
Browser agent BU BenchCan the AI drive a real web browser to finish tasks — clicking, filling forms, and navigating sites the way a person would? Run by Browser Use on their BU Bench task set. Higher is better. | 62% | — |
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. | 33.2%Best | 30.8% |
Abstract reasoning ARC-AGI-2Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | 58.3% | — |
Science GPQA DiamondGraduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 89.9%Best | 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 OSWorld-VerifiedCan the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 72.5% | — |
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% |
Agentic financial analysis Finance Agent v2Tests the AI on real financial-analysis work, like digging through reports and making sound decisions. Higher is better. | 51% | — |
Knowledge work GDPval-AAMeasures how well the AI does economically valuable knowledge work, judged against human experts. Shown as a rating (like a chess Elo) — higher is better. | 1676 | — |
Chart reasoning CharXiv ReasoningCan the AI read and reason about complex charts and figures, not just text? Higher is better. | 72.4% | — |
Multimodal reasoning MMMU-ProA tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | 74.5% | — |
Spatial reasoning Blueprint-Bench 2Can the AI reason about space and layout — for example, understanding a floor plan or blueprint? Higher is better. | 6.7% | — |
Long context MRCR v2 (8-needle) · 128k averageTests whether the AI can find specific details buried inside a very long document (around 128k tokens — roughly a long book). Higher is better. | 84.9% | — |
Community preference Arena Elo (Text)Real people chat with two anonymous AIs side by side and vote for the answer they prefer. Votes become a chess-style Elo rating on arena.ai — it measures which AI people actually like, not test scores. Higher is better. | 1472 | — |
Community preference (code) Arena Elo (Code)Like the text arena, but people vote on which AI writes better code. The votes become a chess-style Elo rating on arena.ai. Higher is better. | 1521 | — |
| Overview | ||
| Company | Anthropic | Qwen |
| Release date | Feb 17 2026 | Aug 14 2026 |
| Access | Proprietary | Open Weight |
Which is better: Claude Sonnet 4.6 or Qwen3.8-27B?
Claude Sonnet 4.6 leads Qwen3.8-27B on 2 of the 3 benchmarks they both report (DeepSWE 1.1, Humanity's Last Exam, GPQA Diamond). Claude Sonnet 4.6 shipped 178 days before Qwen3.8-27B, so benchmark comparisons should account for the intervening progress.
Claude Sonnet 4.6 is proprietary, while Qwen3.8-27B is open weight.
On DeepSWE 1.1, Qwen3.8-27B leads at 42.2% vs Claude Sonnet 4.6 at 30%. On Humanity's Last Exam · no tools, Claude Sonnet 4.6 leads at 33.2% vs Qwen3.8-27B at 30.8%. On GPQA Diamond, Claude Sonnet 4.6 leads at 89.9% vs Qwen3.8-27B at 89.2%.
Frequently asked questions
Claude Sonnet 4.6 was released by Anthropic on Feb 17 2026.
Qwen3.8-27B was released by Qwen on Aug 14 2026.
Qwen3.8-27B leads on DeepSWE 1.1 — Claude Sonnet 4.6 30% vs Qwen3.8-27B 42.2%.
Claude Sonnet 4.6 leads on Humanity's Last Exam · no tools — Claude Sonnet 4.6 33.2% vs Qwen3.8-27B 30.8%.
Claude Sonnet 4.6 is a proprietary model released by Anthropic. Qwen3.8-27B is an open weight model released by Qwen.
Other comparisons
Claude Sonnet 4.6vsGPT-5.6-CyberQwen3.8-27BvsGPT-5.6-CyberClaude Sonnet 4.6vsGemini 3.7 FlashQwen3.8-27BvsGemini 3.7 FlashClaude Sonnet 4.6vsMuse GlimmerQwen3.8-27BvsMuse GlimmerClaude Sonnet 4.6vsGrok 4.6Qwen3.8-27BvsGrok 4.6Claude Sonnet 4.6vsDeepSeek-V4-Pro-0813Qwen3.8-27BvsDeepSeek-V4-Pro-0813Claude Sonnet 4.6vsMistral Medium 3.5Qwen3.8-27BvsMistral Medium 3.5