Claude Fable 5.1 vs Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)
Wins 2 of 5 areas
Coding · Long documents
Wins 1 of 5 areas
Agents
Claude Fable 5.1 wins more areas, narrowly.Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is cheaper and better at agents.
Scores updated · 10 tests both models report · How we compare
Where each one wins
Tests won in each of the five areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
- CodingWriting and fixing software10Claude Fable 5.11 of 1 test
- Long documentsFinding answers in very long texts10Claude Fable 5.11 of 1 test
- AgentsCarrying out multi-step tasks on its own02Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)2 of 2 tests
- ReasoningHard problems that need careful thinking11Even1 each
- FactsGetting facts right instead of making them up11Even1 each
Coding and long documents rest on a single test each.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) costs 80% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where Claude Fable 5.1 pulls ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+13.2points ahead
- Very hard expert questions across many subjectsHumanity's Last Exam+4.1points ahead
- Reasons across sets of long documentsAA-LCR+2.6points ahead
Where Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+25.6points ahead
- Complex command-line tasks across many fieldsTerminal-Bench 4.0+11.6points ahead
- Real work tasks from 44 professionsGDPVal+4.2points ahead
Every test, side by side
All 10 tests both models report. The winning score is in its model's colour; marks a score checked independently.
AgentsClaude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)
- Terminal-Bench 4.0Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) by 11.65263.6+11.6
- GDPValClaude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) by 4.262.867+4.2
ReasoningEven
- Humanity's Last ExamClaude Fable 5.1 by 4.159.155+4.1
- CritPtClaude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) by 1.729.731.4+1.7
FactsEven
- AA-Omniscience · Non-hallucinationClaude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) by 25.627.453+25.6
- AA-Omniscience · AccuracyClaude Fable 5.1 by 13.267.254+13.2
Other results2 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- AA-OmniscienceClaude Fable 5.1 by 11.243.532.3+11.2
- AA IntelligenceClaude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) by 2.653.456+2.6
Questions people ask
Which is better, Claude Fable 5.1 or Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)?
Claude Fable 5.1 wins two of the five areas where both have results: coding and long documents. Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) wins agents, and costs 80% less. They are level on reasoning and facts.
Which is better for coding?
Claude Fable 5.1. It wins the one coding test both models report.
Which is cheaper?
Claude Fable 5.1 costs $10.00 per million input tokens and $50.00 per million output tokens; Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) costs $2.00 and $10.00. That makes Claude Sonnet 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) about 80% cheaper for the same work.
How do you compare the two?
We use the 10 benchmark tests both models have published scores on. The verdict counts the 8 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 2 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.