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Claude Fable 5.1

Anthropic

Strongest in Academic knowledge (#1 of 123), weakest in Cybersecurity (#22 of 47). Above par in 28 of 28 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 5.5 and Gemini 4 Argon and ahead of Claude Fable 5 and GPT-6.1 Sol.

§ 1 · Profile

What it is good at

Bars run from 50 — the average of the models each source lists — so right of the line is above par. The middle column is the gap to whoever leads that scope.

Knowledge62.4#2/197
Academic knowledge63.9#1/123
Document parsing62.6#3/83
Reasoning64.2#3/195
Mathematics63.7#2/152
Reasoning65.5#7/147
Science62.1#9/122
Agents64.2#3/298
Long-horizon work70.2#3/31
Knowledge work68.1#6/208
Web research57.9#8/35
Computer use61.5#12/68
Coding63.4#3/179
Agentic coding63.9#3/173
Professional60.3#4/194
Document design63.3#3/31
Medical62.6#4/149
Legal62.6#6/173
Finance59.6#6/162
IT operations56.4#10/33
Cybersecurity54.9#22/47
Human preference66.6#7/354
Human preference66.6#7/354
Core abilities61.2#10/199
Language65#3/62
Data analysis58.9#7/31
Instruction following58.9#16/62
General intelligence61.7#20/178

§ 2 · Head to head

What it beats, and what beats it

The same models turn up scope after scope. Counted once: where both were placed, who finished higher. Bars run right for Claude Fable 5.1, left for the other.

GPT-4o miniwon 17 · lost 0
O4 Miniwon 17 · lost 0
Gemini 2.5 Flashwon 17 · lost 0
Grok 4won 17 · lost 0
Claude Haiku 4.5won 17 · lost 0
GPT-4.1won 17 · lost 0
Kimi K2won 17 · lost 0
DeepSeek R1won 17 · lost 0
Qwen3 235B A22B Instructwon 17 · lost 0
GLM-4.6won 17 · lost 0
Mistral Medium 3.5won 17 · lost 0
GPT-4.1 nanowon 18 · lost 0
GPT OSS 120Bwon 18 · lost 0
GPT-4.1 miniwon 18 · lost 0
DeepSeek V3won 18 · lost 0
Mistral Large 3won 18 · lost 0
DeepSeek V3.2won 18 · lost 0
O3won 18 · lost 0
Gemini 3.1 Flash-Litewon 18 · lost 0
GPT-5won 18 · lost 0
Grok 4.3won 18 · lost 0
Qwen3.6 Pluswon 18 · lost 0
Gemini 2.5 Prowon 18 · lost 0
GPT-5 miniwon 19 · lost 0
Claude Sonnet 4won 19 · lost 0
Inkling Smallwon 19 · lost 0
GPT-5.2won 19 · lost 0
GPT-5.4 miniwon 19 · lost 0
Claude Sonnet 4.5won 19 · lost 0
Step 5won 20 · lost 0
Gemma 4 31Bwon 20 · lost 0
GLM-5.2won 20 · lost 0
GPT-5.4 nanowon 21 · lost 0
GPT-5.4won 21 · lost 0
Mistral Large 4won 22 · lost 0
Gemini 3.5 Flash-Litewon 22 · lost 0
Claude Sonnet 5won 22 · lost 0
Inklingwon 26 · lost 0
Qwen3.8 27Bwon 27 · lost 0
GLM-5.3 Flashwon 28 · lost 0
GPT-5.6 Terrawon 27 · lost 1
Claude Haiku 5.5won 25 · lost 1
GPT-6 Lunawon 25 · lost 1
DeepSeek V4.1 Flashwon 25 · lost 1
Kimi K3won 25 · lost 1
GPT-5.6 Lunawon 22 · lost 1
MiniMax M3won 21 · lost 1
DeepSeek V4 Prowon 21 · lost 1
MiMo V2.6 Prowon 21 · lost 1
GLM-5.3won 21 · lost 1
DeepSeek V4 Flashwon 20 · lost 1
Gemini 3.5 Flashwon 20 · lost 1
Claude Opus 4.8won 20 · lost 1
Claude Opus 4.7won 20 · lost 1
Claude Sonnet 4.6won 19 · lost 1
Kimi K2.5won 18 · lost 1
Kimi K2.6won 18 · lost 1
Qwen3.7 Maxwon 18 · lost 1
Claude Opus 4.5won 18 · lost 1
Gemini 3 Prowon 16 · lost 1
Gemini 3.8 Flashwon 26 · lost 2
Grok 4.6won 24 · lost 2
Qwen3.8 Maxwon 24 · lost 2
Grok 4.7won 22 · lost 2
Grok 4.5won 21 · lost 2
Muse Spark 1.3won 21 · lost 2
GPT-5.5won 20 · lost 2
Gemini 3.6 Flashwon 19 · lost 2
GPT-6 Solwon 18 · lost 2
Gemini 3.1 Prowon 18 · lost 2
Kimi K3.1 Prowon 17 · lost 2
Muse Spark 1.1won 17 · lost 2
Muse Spark 1.2won 17 · lost 2
Claude Sonnet 5.5won 23 · lost 3
GPT-5.6 Solwon 21 · lost 3
Gemini 3.7 Flashwon 19 · lost 3
Claude Opus 4.6won 16 · lost 3
GPT-6.1 Terrawon 13 · lost 4
Muse Wonderwon 15 · lost 6
Claude Opus 5won 15 · lost 7
GPT-6 Astrawon 17 · lost 9
GPT-6.1 Solwon 17 · lost 9
Claude Fable 5won 13 · lost 10
Gemini 4 Argonwon 9 · lost 13
Claude Opus 5.5won 10 · lost 15

§ 3 · Sources

Where the numbers come from

10 publications, 42 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1503
GDPval-AA ↗1 measureread 2026-11-10
GDPval-AA 1763
AA-Briefcase ↗1 measureread 2026-11-10
AA-Briefcase 1669
Terminal-Bench ↗1 measureread 2026-11-10
Terminal-Bench 57.6% (Claude Code)
ARC-AGI-2 ↗1 measureread 2026-11-10
ARC-AGI-2 90%
LiveBench ↗8 measuresread 2026-11-10
LiveBench 84LiveBench · Agentic 74.2LiveBench · Reasoning 91.7LiveBench · Coding 89.7LiveBench · Browser Use 89.8LiveBench · Data Analysis 80.3LiveBench · Research 88.5LiveBench · Design 81.6
LiveBench 1.0 ↗8 measuresread 2026-11-10
LiveBench 1.0 83.4LiveBench 1.0 · Reasoning 91.7LiveBench 1.0 · Coding 86.4LiveBench 1.0 · Agentic Coding 66.1LiveBench 1.0 · Mathematics 97LiveBench 1.0 · Data Analysis 80.3LiveBench 1.0 · Language 89.5LiveBench 1.0 · Instruction Following 73
SimpleBench ↗1 measureread 2026-11-10
SimpleBench 86.6%
Vals.ai ↗14 measuresread 2026-11-10
Vals · Legal Research Bench 55.29%Vals · LegalBench 88.51%Vals · Finance Agent 58.88%Vals · TaxEval 75.96%Vals · MortgageTax 70.79%Vals · MedCode 53.51%Vals · MedScribe 91.29%Vals · CyberBench 70.42%Vals · SRE Bench 22.9%Vals · Vibe Code Bench 90.26% (OpenHands)Vals · Code Migration 54.61%Vals · GPQA Diamond 93.43%Vals · MMLU Pro 92.38%Vals · ProofBench 100%
ParseBench ↗6 measuresread 2026-11-10
ParseBench · Overall 77.81%ParseBench · Tables 91.53%ParseBench · Charts 66.93%ParseBench · Content faithfulness 90.77%ParseBench · Semantic formatting 76.02%ParseBench · Visual grounding 63.81%

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