Models / Anthropic/ Claude Fable 5

Claude Fable 5

Anthropic · released Jun 9, 2026

Input: text, images and documents. Output: text.InputOutput
Type
Closed
Input
$10.00
Output
$50.00
Cached
$1.00

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

Our take

The case for it

  • 1st of 168 on Arena Coding as of 25 Sep 2026 and 1st of 163 on Arena Maths as of 25 Sep 2026, both from human pairwise votes rather than a correctness rubric.
  • 1st of 58 on LiveBench Language via Max effort as of 25 Jun 2026, with 4th of 58 on LiveBench Data Analysis and 5th of 58 on LiveBench Instruction Following on the same board and date.
  • 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

  • We list no download for it, so using it means choosing a host and paying per token rather than running it yourself.
  • No licence is supplied, so we cannot say what commercial use or redistribution is permitted.
  • 17th of 55 on Arena Agent · Task outcome via High as of 25 Sep 2026, which records whether the session finished the task it set out to do.
00

How good is it?

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

Good at
  • getting answers to everyday questionsArena Text (overall) · 2nd of 168
  • drafts, rewrites and editingArena Creative Writing · 2nd of 168
  • writing and completing codeArena Coding · 1st of 168
  • multi-step work it carries out for youArena Agent · 4th of 55
  • calling tools to carry out requestsArena Agent · Tool use · 9th of 55
  • changing course when you give new instructionsArena Agent · Steerability · 2nd of 55
  • getting back on track after a step failsArena Agent · Recovery · 5th of 55

EverydayGeneral questions and everyday reasoning

5 of 5

Arena Text (overall)2nd of 168 · 1506

Arena Hard Prompts 2nd of 168Arena Maths 1st of 163LiveBench Data Analysis 4th of 58LiveBench Mathematics 7th of 58LiveBench Reasoning 11th of 58

Also on this board: 1504 (Sep 25, 2026). Read the pair, not the higher one.

CodingWriting and fixing code on its own

5 of 5

Arena Coding1st of 168 · 1552

Arena Code (WebDev) 12th of 95LiveBench Coding 4th of 58

Also on this board: 1551 (Sep 25, 2026). Read the pair, not the higher one.

AgenticPlanning, calling tools, staying on task

4 of 5

Arena Agent4th of 55 · 0.083

LiveBench Agentic Coding 9th of 58

WritingDrafting and rewriting prose

4.5 of 5

Arena Creative Writing2nd of 168 · 1504

LiveBench Language 1st of 58

Also on this board: 1501 (Sep 25, 2026). Read the pair, not the higher one.

How it behaves in an agent loop
Tool usereaches for the right one, and does not invent one9th of 55
Steerabilitydoes what it was asked, and changes course when told2nd of 55
Recoverygets back on track after a command fails5th of 55
Task outcomefinishes what the session set out to do17th 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 2nd of 168LiveBench 3rd of 58LiveBench Instruction Following 5th of 58Arena Agent · Steerability 2nd of 55Arena Agent · Recovery 5th of 55Arena Agent · Tool use 9th of 55Arena Agent · Task outcome 17th 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
82.97source ↗
62.17source ↗
85.99source ↗
80.54source ↗
75.77source ↗
90.68source ↗
95.99source ↗
89.65source ↗
0.083source ↗
0.085source ↗
0.116source ↗
0.036source ↗
0.004source ↗
1552source ↗
1504source ↗
1532source ↗
1526source ↗
1506source ↗
1628source ↗
01

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
~42 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
DeepInfraDirect$10.00 / $50.00checked 4 hours ago1Mnot measuredUnknownUnknownUnknown
Microsoft Azure AIThrough OpenRouter$10.00 / $50.00checked 4 hours ago1M128K max reply49 tok/sNoNoUnknown
Google Vertex AIglobalThrough OpenRouter$10.00 / $50.00checked 4 hours ago1M128K max reply56 tok/sNoNoUnknown
Claude Platform on AWSThrough OpenRouter$10.00 / $50.00checked 4 hours ago1M128K max reply6 tok/sNoYes30 daysUnknown
AnthropicDirect$10.00 / $50.00checked 4 hours ago1M128K max reply42 tok/sNoYes30 daysUnknown
Amazon BedrockThrough OpenRouter$10.00 / $50.00checked 4 hours ago1M128K max reply38 tok/sNoNoUnknown
Google Vertex AIeuropeThrough OpenRouter$11.00 / $55.00checked 4 hours ago1M128K max reply59 tok/sNoNoUnknown

Across the 8 listings we hold: 6 say they do not train on prompts, 0 say they do and 2 do 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✓✓✓
DeepInfraDirect
Microsoft Azure AIThrough OpenRouter✓✓✓
Google Vertex AIglobalThrough OpenRouter✓✓✓
Claude Platform on AWSThrough OpenRouter✓✓✓
AnthropicDirect✓✓✓
Amazon BedrockThrough OpenRouter✓✓✗
Google Vertex AIeuropeThrough OpenRouter✓✓✓

Tool calling: 7 of 8 listings say yes, 1 publishes no parameter list. JSON output: 7 of 8 listings say yes, 1 publishes no parameter list. Strict schema: 6 of 8 listings say yes, 1 says no, 1 publishes no parameter list.

02

Models people weigh against Claude Fable 5

03

When we formed this view

Recent changes

Sep 25, 2026BenchmarkScored 0.083 via High on Arena Agent
What movedleaderboard
Sep 25, 2026BenchmarkScored 0.085 via High on Arena Agent · Recovery
What movedleaderboard
Sep 25, 2026BenchmarkScored 0.116 via High on Arena Agent · Steerability
What movedleaderboard
Sep 25, 2026BenchmarkScored 0.036 via High on Arena Agent · Task outcome
What movedleaderboard
Sep 25, 2026BenchmarkScored 0.004 via High on Arena Agent · Tool use
What movedleaderboard
Sep 13, 2026BenchmarkScored 1552 on Arena Coding
What movedleaderboard
Sep 13, 2026BenchmarkScored 1504 on Arena Creative Writing
What movedleaderboard
Sep 13, 2026BenchmarkScored 1532 on Arena Hard Prompts
What movedleaderboard
Sep 13, 2026BenchmarkScored 1511 on Arena Instruction Following
What movedleaderboard
Sep 13, 2026BenchmarkScored 1526 on Arena Maths
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

  • 1 of 8 listings publishes no parameter list, so what its API accepts is unknown to us.
  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 2 of 8 listings do not say whether they train 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

Machine-readable model card (omc.json) →

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