Claude Fable 5vsQwen3.8-27B
Claude Fable 5 | Qwen3.8-27B | |
|---|---|---|
| Specifications | ||
Parameters | — | 27B |
Context window | 1M | 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. | 54% | — |
Prompt injection robustness Gray Swan IPI · k = 1Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. Gray Swan's indirect prompt injection benchmark measures how often such an attack succeeds when the attacker gets a single try. Lower is better. | 0.4% | — |
Prompt injection robustness Gray Swan IPI · k = 10Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. This variant gives the attacker 10 tries and counts an attack as successful if any of them works. Lower is better. | 2.3% | — |
Prompt injection robustness Gray Swan IPI · k = 15Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. This variant gives the attacker 15 tries and counts an attack as successful if any of them works. Lower is better. | 2.8% | — |
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. | 80.3%Best | 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. | 95.5% | — |
Agentic coding CursorBench v3.2Cursor's own test of harder, real-world coding tasks inside a code editor, on the refreshed v3.2 task set. Scores aren't comparable with v3.1. Higher is better. | 70.5% | — |
Agentic coding CursorBench v3.1Cursor's own test of harder, real-world coding tasks inside a code editor. Higher is better. | 72.9% | — |
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. | 70%Best | 42.2% |
Agentic coding DeepSWE 1.0Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. Higher is better. | 66.1% | — |
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. | 92% | — |
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 computer work Frontier-Bench v0.1A hard, ever-evolving set of real computer tasks — coding, system administration, data work, and more — that an AI agent has to complete on its own. Run by the Harbor / Laude Institute team as the successor to Terminal-Bench (v0.1 is the first release of the task set). The score is the share of tasks solved. Higher is better. | 33.8% | — |
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. | 88%Best | 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% |
Web browsing BrowseCompCan the AI browse the web and track down hard-to-find answers? Higher is better. | 86.9% | — |
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% |
Multidisciplinary reasoning Humanity's Last Exam · with toolsHumanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | 64.5% | — |
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 OSWorld-VerifiedCan the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 85% | — |
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 legal work Harvey's Legal Agent BenchmarkHarvey's test of whether an AI agent can complete real legal work — drafting and reviewing documents, working with spreadsheets and presentations, and navigating files the way a lawyer's assistant would. Higher is better. | 11.25% | — |
Tax questions TaxEval v2A set of real tax questions created by Vals AI — can the AI give accurate answers about tax rules and filings? Higher is better. | 76.94% | — |
Medical admin work MedScribeCan the AI support doctors with their administrative work, like notes and paperwork? Created by Vals AI. Higher is better. | 88.52% | — |
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. | 1932 | — |
Knowledge work GDPval-AA v2economically valuable knowledge work (v2, re-based Elo) | 1760 | — |
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. | 1509 | — |
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. | 1631 | — |
| Overview | ||
| Company | Anthropic | Qwen |
| Release date | Jun 9 2026 | Aug 14 2026 |
| Access | Proprietary | Open Weight |
Which is better: Claude Fable 5 or Qwen3.8-27B?
Claude Fable 5 leads Qwen3.8-27B on 3 of the 3 benchmarks they both report (SWE-Bench Pro, DeepSWE 1.1, Terminal-Bench 2.1). Claude Fable 5 shipped 66 days before Qwen3.8-27B, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Fable 5) vs 262k (Qwen3.8-27B). Claude Fable 5 is proprietary, while Qwen3.8-27B is open weight.
On SWE-Bench Pro, Claude Fable 5 leads at 80.3% vs Qwen3.8-27B at 61.7%. On DeepSWE 1.1, Claude Fable 5 leads at 70% vs Qwen3.8-27B at 42.2%. On Terminal-Bench 2.1, Claude Fable 5 leads at 88% vs Qwen3.8-27B at 73%.
Frequently asked questions
Claude Fable 5 was released by Anthropic on Jun 9 2026.
Qwen3.8-27B was released by Qwen on Aug 14 2026.
Claude Fable 5 leads on SWE-Bench Pro — Claude Fable 5 80.3% vs Qwen3.8-27B 61.7%.
Claude Fable 5 has a 1M context window; Qwen3.8-27B has 262k.
Claude Fable 5 is a proprietary model released by Anthropic. Qwen3.8-27B is an open weight model released by Qwen.
Other comparisons
Claude Fable 5vsGPT-5.6-CyberQwen3.8-27BvsGPT-5.6-CyberClaude Fable 5vsGemini 3.7 FlashQwen3.8-27BvsGemini 3.7 FlashClaude Fable 5vsMuse GlimmerQwen3.8-27BvsMuse GlimmerClaude Fable 5vsGrok 4.6Qwen3.8-27BvsGrok 4.6Claude Fable 5vsDeepSeek-V4-Pro-0813Qwen3.8-27BvsDeepSeek-V4-Pro-0813Claude Fable 5vsMistral Medium 3.5Qwen3.8-27BvsMistral Medium 3.5