Claude Fable 5.1

Made by Anthropic, released 1 Sep 2026. Epoch AI lists its access as “API access”. Appears strongest at coding, knowledge, maths and writing among the models listed here.

Find my AI Compare with another model

In short

What it does well

  • Coding: Top tier (6th of 77 listed models)
  • Knowledge: Top tier (5th of 43 listed models)
  • Maths: Top tier (4th of 43 listed models)
  • Writing: Top tier (3rd of 77 listed models)

Where it falls short

The four main ratings show no weakness. That is not evidence it has none.

What we don't know yet

  • Graduate-level science questions: Not enough data
  • Fixing real software bugs: Not enough data

The four ratings

  • Top tier
  • Strong
  • Middle
  • Behind the leaders
  • Not enough data

Ratings compare only the 77 models listed here, in quarters, best first. “Not enough data” means no result yet. It is never a low score.

Writing
Top tierHow often people preferred its answers to writing prompts. 1,512 on Arena's scale · Source for Claude Fable 5.1 writing score (lmarena)
Coding
Top tierHow often people preferred its answers to coding questions. 1,530 on Arena's scale · Source for Claude Fable 5.1 coding score (lmarena)
Maths
Top tierHow many very hard maths problems it solved. 90.2% · Source for Claude Fable 5.1 maths score (epoch)
Knowledge
Top tierHow many short factual questions it answered correctly. 70.8% · Source for Claude Fable 5.1 knowledge score (epoch)

Evidence completeness: Broad evidence, 11 of 13 tests have a result.

Where it is relatively stronger or weaker

This compares each kind of request with the model's own overall position among the 77 listed models, using Arena's votes. It is about performance on different languages, kinds of request and topics, not about political or social bias.

Relatively stronger

No category stands out as clearly stronger than its overall position.

Relatively weaker

No category stands out as clearly weaker than its overall position.

Show every category we can see
Position in each Arena category
CategoryPositionArena scoreVotesSource
Expert-level prompts
Kind of request
4th of 771,545
95% range 1,529 to 1,561
1,497Source for Expert-level prompts
Hard prompts
Kind of request
3rd of 771,529
95% range 1,522 to 1,536
9,970Source for Hard prompts
Long prompts
Kind of request
3rd of 771,525
95% range 1,517 to 1,533
7,062Source for Long prompts
Longer conversations
Kind of request
10th of 771,495
95% range 1,482 to 1,508
2,293Source for Longer conversations
Chinese
Language
3rd of 761,581
95% range 1,564 to 1,598
1,347Source for Chinese
English prompts
Language
4th of 771,508
95% range 1,500 to 1,516
6,916Source for English prompts
French
Language
2nd of 721,521
95% range 1,495 to 1,546
608Source for French
German
Language
9th of 551,496
95% range 1,462 to 1,529
322Source for German
Japanese
Language
1st of 541,562
95% range 1,527 to 1,597
329Source for Japanese
Non-English prompts
Language
2nd of 771,510
95% range 1,503 to 1,516
10,256Source for Non-English prompts
Russian
Language
2nd of 771,521
95% range 1,508 to 1,534
2,256Source for Russian
Spanish
Language
2nd of 701,518
95% range 1,494 to 1,542
568Source for Spanish
Entertainment, sport and media
Topic
3rd of 771,499
95% range 1,489 to 1,509
4,381Source for Entertainment, sport and media
Law and government
Topic
3rd of 761,513
95% range 1,496 to 1,529
1,398Source for Law and government
Medicine and health
Topic
2nd of 751,535
95% range 1,518 to 1,552
1,308Source for Medicine and health
Science
Topic
2nd of 771,535
95% range 1,523 to 1,546
2,869Source for Science
Software and IT
Topic
3rd of 771,529
95% range 1,521 to 1,538
5,644Source for Software and IT

Bias: what we can and can't see

Our sources do not measure political lean, stereotyping, flattery (agreeing with you too readily) or safety behaviour, so we cannot say how any model does on those. What we can show is above: where a model is relatively stronger or weaker across languages, kinds of request and topics. Also, people voting in Arena can favour answer style, such as length and formatting, and our numbers do not adjust for that. See what AI bias means and what these tests can tell you.

Best-supported use cases

Where an alternative might be more suitable

It is rated Top tier on every main test where it has a result.

What it is

Maker
Anthropic
Release date (Epoch AI)
1 Sep 2026
Access, as listed by Epoch AI
API access
Licence, as listed by Arena
Proprietary
Maker's country (Epoch AI)
United States of America
Last observation in our data
28 Oct 2026
Data last changed
29 Oct 2026, 14:36 UTC

No GPQA Diamond result for this model in the Epoch data at retrieval.

We have not verified an official product page for this model, so we do not link to one.

How you can use it

Proprietary. The model's files are not published, so it is generally available only through its maker or partners the maker chooses.

How you can reach it (an app, a website, a developer API or a third-party tool) and what that costs are not covered by our benchmark data. Where we could verify prices from the maker's own pages, they are shown under Price. Epoch AI lists access as “API access”. See models, apps and harnesses and how AI pricing works.

Price

Price not independently verified

What Anthropic's own page says about the Fable family (USD ($ as shown; the page does not state a currency code); checked 28 Oct 2026)

  • Free ($0): Fable not available
  • Pro ($20 per month billed monthly, or $17 per month billed annually ($200 up front)): Fable usage credits
  • Max (From $100 per month): Fable 50% of weekly limits

The page marks plans against model families, not versions, so it does not say which version of a family a plan includes. Check that before relying on it.

See Claude plans and pricing (checked 28 Oct 2026). Page opened and read.

We never infer subscription prices from API prices. New to “tokens” and “per million”? See how AI pricing works.

Good to remember

  • Benchmarks are samples of tasks. None proves performance in every situation.
  • Arena scores come from people choosing between answers. That measures preference, not correctness.
  • Ratings are relative to the 77 models listed here. A different set would change them.
  • Sources test models at different settings. Each result shows the setting used, and we do not adjust it.

The evidence, for the curious

Show all 13 tests with settings and sources
All published results for Claude Fable 5.1. Ratings compare only the 77 models on this site.
TestResultRatingSetting usedSource identifierObservedLinks
Arena text: overall preference
Arena 'text' leaderboard (Bradley-Terry rating, no style control)
1,514
Arena score
95% range 1,508 to 1,520, 17,178 votes
Top tier effort: Max, bradley-terry rating Claude Fable 5.1 (Max)
lmarena · text/latest
28 Oct 2026 Source for Claude Fable 5.1 Arena text: overall preference score (lmarena)
Arena text: creative writing
Arena 'text' leaderboard, category creative_writing
1,512
Arena score
95% range 1,501 to 1,523, 3,884 votes
Top tier effort: Max, bradley-terry rating Claude Fable 5.1 (Max)
lmarena · text/latest
28 Oct 2026 Source for Claude Fable 5.1 Arena text: creative writing score (lmarena)
Arena text: coding
Arena 'text' leaderboard, category coding
1,530
Arena score
95% range 1,519 to 1,541, 3,403 votes
Top tier effort: Max, bradley-terry rating Claude Fable 5.1 (Max)
lmarena · text/latest
28 Oct 2026 Source for Claude Fable 5.1 Arena text: coding score (lmarena)
Arena text: maths
Arena 'text' leaderboard, category math
1,531
Arena score
95% range 1,511 to 1,551, 835 votes
Top tier effort: Max, bradley-terry rating Claude Fable 5.1 (Max)
lmarena · text/latest
28 Oct 2026 Source for Claude Fable 5.1 Arena text: maths score (lmarena)
Arena text: following instructions
Arena 'text' leaderboard, category instruction_following
1,519
Arena score
95% range 1,510 to 1,528, 5,162 votes
Top tier effort: Max, bradley-terry rating Claude Fable 5.1 (Max)
lmarena · text/latest
28 Oct 2026 Source for Claude Fable 5.1 Arena text: following instructions score (lmarena)
Arena text: business and management
Arena 'text' leaderboard, category industry_business_and_management_and_financial_operations
1,494
Arena score
95% range 1,483 to 1,505, 3,066 votes
Top tier effort: Max, bradley-terry rating Claude Fable 5.1 (Max)
lmarena · text/latest
28 Oct 2026 Source for Claude Fable 5.1 Arena text: business and management score (lmarena)
Arena WebDev: building web apps
Arena 'webdev' leaderboard (Code Arena), category overall
1,746
Arena score
95% range 1,737 to 1,754, 8,614 votes
Top tier effort: Max, bradley-terry rating Claude Fable 5.1 (Max)
lmarena · webdev/latest
28 Oct 2026 Source for Claude Fable 5.1 Arena WebDev: building web apps score (lmarena)
FrontierMath Tiers 1-3 (v2)
FrontierMath Tiers 1-3 v2 (private set), benchmark released 2026-06-12
90.2%
share of problems solved
standard error ±1.8 points
Top tier effort: max, best score across scorers claude-fable-5-1_max
epoch · frontiermath_tiers_1_3_v2.csv
1 Sep 2026 Source for Claude Fable 5.1 FrontierMath Tiers 1-3 (v2) score (epoch)
No public run log in the data file.
OTIS Mock AIME 2024-2025
OTIS Mock AIME 2024-2025, benchmark released 2024-12-19
100.0%
share of problems solved
standard error ±0.0 points
Top tier effort: max, best score across scorers claude-fable-5-1_max
epoch · otis_mock_aime_2024_2025.csv
1 Sep 2026 Source for Claude Fable 5.1 OTIS Mock AIME 2024-2025 score (epoch)
No public run log in the data file.
GPQA DiamondNot enough data
SimpleQA Verified
SimpleQA Verified, benchmark released 2025-09-09
70.8%
share of questions correct
standard error ±1.4 points
Top tier effort: max, best score across scorers claude-fable-5-1_max
epoch · simpleqa_verified.csv
1 Sep 2026 Source for Claude Fable 5.1 SimpleQA Verified score (epoch)
No public run log in the data file.
SWE-bench Verified (Epoch runs)Not enough data
FrontierCode (reported by Cognition)
FrontierCode, benchmark released 2026-06-08, aggregation Mean@5
50.9%
mean score over 5 attempts
no uncertainty figure published
Not rated (results use different tools) effort: medium, tool: claude-code, mean@5 claude-fable-5-1_medium
epoch · frontiercode_external.csv
not provided Source for Claude Fable 5.1 FrontierCode (reported by Cognition) score (epoch) · Run details for FrontierCode (reported by Cognition)

Missing evidence

Not enough data for these tests:

  • GPQA Diamond
  • SWE-bench Verified (Epoch runs)

Missing results are not low scores and do not count against the model.

Where a source gives no public run log, we cannot show the run behind the score. See data sources.

Not sure this is the right one?

Tell us what you need help with and we'll narrow the options down.

Find my AI