Models / Anthropic/ Claude Fable 5.1

Claude Fable 5.1

Anthropic · released Sep 1, 2026

Input: text, images and documents. Output: text.InputOutput
Type
Closed
Input
$10.00
Output
$50.00
Cached
$0.25

List price · per 1M tokens · Anthropic at 1M context · machine-readable source ↗

Our take

Written Oct 1, 2026

Claude Fable 5.1 is a hosted-only model: we list no download for it, so using it means choosing a host. It leads the agentic boards we record, and its weakest measured area is tool use, where it sits in the bottom half of the same field.

Who should pick it

Reach for it in agentic sessions where the model has to finish a task and recover when a command fails, or for long-document work where splitting files first is a nuisance. It takes text, images and files alongside the question. Skip it if you need to run the model on your own hardware, or if calling the right tool without inventing one is the core of your workflow.

The case for it

  • 1st of 55 on Arena Agent via Max as of 25 Sep 2026, and 1st of 58 on LiveBench via Max effort as of 25 Jun 2026, so it is the one to start with when a task has to be carried through rather than answered.
  • 97.01% on LiveBench Mathematics and 91.69% on LiveBench Reasoning at Max effort, both competition-style set-piece tasks rather than open-ended project work.
  • The request capacity is large enough that long documents need not be split up first, though reliable recall across all of it is unverified in our data.
  • Text, image and file input with written output, so a screenshot or a document does not have to be described in words first.

The case against it

  • 24th of 55 on Arena Agent · Tool use via Max as of 25 Sep 2026, an inverse-propensity score for calling the right tool and not inventing one, placing it in the bottom half of that field.
  • 15th of 168 on Arena Coding via Max as of 25 Sep 2026, well behind its 3rd of 168 on Arena Text (overall) and 4th of 168 on Arena Creative Writing.
  • We list no download for it, so using it means choosing a host; all five hosts list the same rate, so price does not pick one for you.
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How good is it?

A closed text model for everyday questions, drafting, coding and multi-step agent work.

Good at
  • getting answers to everyday questionsArena Text (overall) · 3rd of 168
  • drafts, rewrites and editingArena Creative Writing · 4th of 168
  • writing and completing codeArena Coding · 15th of 168
  • multi-step work it carries out for youArena Agent · 1st of 55
  • changing course when you give new instructionsArena Agent · Steerability · 6th of 55
  • getting back on track after a step failsArena Agent · Recovery · 2nd of 55

EverydayGeneral questions and everyday reasoning

4.5 of 5

Arena Text (overall)3rd of 168 · 1501

Arena Hard Prompts 4th of 168Arena Maths 5th of 163LiveBench Mathematics 2nd of 58LiveBench Reasoning 3rd of 58LiveBench Data Analysis 6th of 58

CodingWriting and fixing code on its own

4.5 of 5

Arena Coding15th of 168 · 1529

Arena Code (WebDev) 3rd of 95LiveBench Coding 3rd of 58

AgenticPlanning, calling tools, staying on task

5 of 5

Arena Agent1st of 55 · 0.138

LiveBench Agentic Coding 3rd of 58

WritingDrafting and rewriting prose

4 of 5

Arena Creative Writing4th of 168 · 1484

LiveBench Language 2nd of 58
How it behaves in an agent loop
Tool usereaches for the right one, and does not invent one24th of 55
Steerabilitydoes what it was asked, and changes course when told6th of 55
Recoverygets back on track after a command fails2nd of 55
Task outcomefinishes what the session set out to do1st of 55

Placings on Arena's agent boards, from live sessions people ran themselves. A model can lead on one of these and sit mid-field on the others.

Other boards it appears on
Arena Instruction Following 4th of 168LiveBench 1st of 58LiveBench Instruction Following 15th of 58Arena Agent · Task outcome 1st of 55Arena Agent · Recovery 2nd of 55Arena Agent · Steerability 6th of 55Arena Agent · Tool use 24th of 55

Boards this model appears on that none of the ratings above are built on.

Every published score for this model20 scoresEvery figure we hold, from 20 boards, with who ran it and a link to the source — including the boards no rating above is built on.
LiveBenchreasoning
83.41source ↗
66.06source ↗
86.38source ↗
80.28source ↗
72.99source ↗
89.5source ↗
97.01source ↗
91.69source ↗
0.138source ↗
0.117source ↗
0.074source ↗
0.173source ↗
0.004source ↗
1529source ↗
1484source ↗
1520source ↗
1497source ↗
1517source ↗
1501source ↗
1751source ↗
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Where to rent it

Prices checked 4 hours ago — each listing carries its own date.

Cheapest published offer

Anthropic, direct

The lab is also the cheapest we hold. The strip above and this offer are the same one, so nothing on this page undercuts Anthropic on 1M of context.

per 1M tokens
$10.00 in / $50.00 out
Context served
1M
Throughput
~51 tok/s
Current provider offers with price, context and prompt-privacy answers
ProviderIn / out per 1M tokensContextThroughputTrains on promptsLogs promptsZero retention
OpenRouterOpenRouter's own listing$10.00 / $50.00checked 4 hours ago1Mnot measuredUnknownUnknownUnknown
Microsoft Azure AIThrough OpenRouter$10.00 / $50.00checked 4 hours ago1M128K max reply45 tok/sNoNoUnknown
Google Vertex AIglobalThrough OpenRouter$10.00 / $50.00checked 4 hours ago1M128K max reply62 tok/sNoNoUnknown
AnthropicDirect$10.00 / $50.00checked 4 hours ago1M128K max reply51 tok/sNoYes30 daysUnknown
Amazon BedrockThrough OpenRouter$10.00 / $50.00checked 4 hours ago1M128K max reply50 tok/sNoNoUnknown

Across the 5 listings we hold: 4 say they do not train on prompts, 0 say they do and 1 does not say. 0 appear in the zero-retention registry we check; the rest are unknown to us.

What each host's API supports

From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.

API features per host
ProviderTool callingJSON outputStrict schema
OpenRouterOpenRouter's own listing✓✓✓
Microsoft Azure AIThrough OpenRouter✓✓✓
Google Vertex AIglobalThrough OpenRouter✓✓✓
AnthropicDirect✓✓✓
Amazon BedrockThrough OpenRouter✓✓✗

Tool calling: 5 of 5 listings say yes. JSON output: 5 of 5 listings say yes. Strict schema: 4 of 5 listings say yes, 1 says no.

02

Models people weigh against Claude Fable 5.1

03

When we formed this view

Recent changes

Sep 25, 2026ListedListed on LLMap
What movedfirst indexed by our pipeline
Sep 25, 2026BenchmarkScored 0.138 via Max on Arena Agent
What movedleaderboard
Sep 25, 2026BenchmarkScored 0.117 via Max on Arena Agent · Recovery
What movedleaderboard
Sep 25, 2026BenchmarkScored 0.074 via Max on Arena Agent · Steerability
What movedleaderboard
Sep 25, 2026BenchmarkScored 0.173 via Max on Arena Agent · Task outcome
What movedleaderboard
Sep 25, 2026BenchmarkScored 0.004 via Max on Arena Agent · Tool use
What movedleaderboard
Sep 25, 2026BenchmarkScored 1529 via Max on Arena Coding
What movedleaderboard
Sep 25, 2026BenchmarkScored 1484 via Max on Arena Creative Writing
What movedleaderboard
Sep 25, 2026BenchmarkScored 1520 via Max on Arena Hard Prompts
What movedleaderboard
Sep 25, 2026BenchmarkScored 1497 via Max on Arena Instruction Following
What movedleaderboard

Each date is the day we first saw the change, or the day the maker announced it.

What we do not know about this model yet

  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 1 of 5 listings does not say whether it trains on prompts.
  • We hold no batch or off-peak rate for any of its listings.
04

Licence and identifiers

What the licence allowsWe hold no licence record for this model. Inside are the identifiers you need to pull it — its Hugging Face repo where we have one, our slug and a machine-readable card.

Licence

We hold no licence record for this model, and no record of published weights either — so we can neither summarise its terms nor point you at the weights.

Identifiers

Takes in, gives back
Text, images and documents in, text out
Catalogue slug
anthropic-claude-fable-5-1

Machine-readable model card (omc.json) →

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