Pass IndexThe State of AISign in

Claude Fable 5.1

Claude Fable 5.1 improves on Fable 5 across long-running agentic coding, knowledge work, and research, following instructions precisely over sessions that run unattended for hours.

text + image + file → text · made by Anthropic

$10→$50per Mtok in / out
Anthropic · 13 sellers

Sold by 31 ways

SellerLaneRate
AWS Bedrock cloudbatch$5per Mtok in$25per Mtok outraw.githubusercontent.com · read 2026-10-31
Databricks cloudstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writeraw.githubusercontent.com · read 2026-10-31
AWS Bedrock cloudstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writemodels.dev · read 2026-10-31
Google Vertex AI cloudstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writemodels.dev · read 2026-10-31
Nous Research 2 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache write
Nous Research aggregatorbatch$5per Mtok in$25per Mtok out$0.12per Mtok cached$6.25per Mtok cache writeinference-api.nousresearch.com · read 2026-09-20
Nous Research aggregatorstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writeinference-api.nousresearch.com · read 2026-09-20
OpenRouter 6 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache write
OpenRouter aggregatorbatch$5per Mtok in$25per Mtok out$0.12per Mtok cached$6.25per Mtok cache writeopenrouter.ai · read 2026-09-20
OpenRouter aggregatorstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writeopenrouter.ai · read 2026-09-02
OpenRouter aggregatoramazon-bedrock$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writeopenrouter.ai · read 2026-09-20
OpenRouter aggregatoranthropic$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writeopenrouter.ai · read 2026-09-20
OpenRouter aggregatorazure$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writeopenrouter.ai · read 2026-09-20
OpenRouter aggregatorgoogle-vertex/global$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writeopenrouter.ai · read 2026-09-20
Anthropic aggregatorstandard$10per Mtok in$50per Mtok out$0.25per Mtok cacheddocs.claude.com · read 2026-10-31
DigitalOcean aggregatorstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writemodels.dev · read 2026-10-31
ElectronHub aggregatorstandard$10per Mtok in$50per Mtok outapi.electronhub.ai · read 2026-10-31
GitHub Copilot aggregatorstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writemodels.dev · read 2026-10-31
Microsoft Azure AI aggregatorstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writemodels.dev · read 2026-10-31
Requesty 2 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
Requesty aggregatoranthropic$10per Mtok in$50per Mtok out$0.25per Mtok cachedrouter.requesty.ai · read 2026-09-20
Requesty aggregatorvertex$10per Mtok in$50per Mtok out$0.25per Mtok cachedrouter.requesty.ai · read 2026-09-20
Venice AI aggregatorstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writemodels.dev · read 2026-10-31
Vercel AI Gateway aggregatorstandard$10per Mtok in$50per Mtok out$0.25per Mtok cached$12.5per Mtok cache writeai-gateway.vercel.sh · read 2026-09-20
amazon-bedrock 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
amazon-bedrock aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
azure-cognitive-services 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
azure-cognitive-services aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
edenai 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
edenai aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
google-vertex 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
google-vertex aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
google-vertex-anthropic 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
google-vertex-anthropic aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
kilo 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
kilo aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
llmgateway 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
llmgateway aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
llmgateway-providers 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
llmgateway-providers aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
merge-gateway 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
merge-gateway aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02
nano-gpt 0 ways$10per Mtok in$50per Mtok out$0.25per Mtok cached
nano-gpt aggregatornot on the seller's list todaystandard$10per Mtok in$50per Mtok out$0.25per Mtok cachedmodels.dev · read 2026-09-02

Measured 57 standings

PlaceBoardMetricScore
1stof 131Artificial Analysis · Agentic IndexIndex57.2
1stof 163Artificial Analysis · Coding IndexIndex80.7
1stof 61Design Arena · fullstack (agents)Elo1326
1stof 50Design Arena · godotgamedev (agents)Elo1327
1stof 36Design Arena · htmlslides (agents)Elo1394
1stof 41Design Arena · python-pptxslides (agents)Elo1318
1stof 41Design Arena · spreadsheet (agents)Elo1416
1stof 42Gso — Epoch AIScore OPT@10.882
1stof 84Proofbench — Epoch AIAccuracy (max)100
2ndof 282ARC-AGI-2 (Public Eval)Score (%) (xhigh)99.17
2ndof 56Humanity's Last Exam (Epoch AI replication)Accuracy (xhigh)46.5
2ndof 30Mirrorcode — Epoch AImean_score (max)93.333
3rdof 68Design Arena · webapps (agents)Elo1298
3rdof 18Rli — Epoch AIScore17.92
3rdof 173Weirdml — Epoch AIAccuracy (max)92.9
4thof 21Frontierswe — Epoch AIScore (max)56.291
4thof 235Scicode — Epoch AIScore (max)63.079
5thof 273ARC-AGI-1 (Public Eval)Score (%) (max)99
5thof 60Apex agents — Epoch AIPass@1 score0.686
5thof 28Ebr bench — Epoch AImean_score (max)57.143
5thof 122Frontiermath tiers 1 3 v2 — Epoch AImean_score (max)90.175
5thof 53LMArena · AgentNet Improvement (%)12.66
5thof 141LMArena · WebDevScore (Elo) (max)1745
5thof 135Webdev arena — Epoch AIArena Score (max)1758.05
5thof 25Weirdml v3 — Epoch AIScore (xhigh)25.97
6thof 35Blueprint bench 2 — Epoch AIScore41.866
6thof 235Dtbench — Epoch AIAccuracy97.6
6thof 46Frontiercode — Epoch AIMain score (medium)0.509
6thof 414LMArena · TextScore (Elo) (max)1501
6thof 93Simpleqa verified — Epoch AImean_score (max)70.8
7thof 150Design Arena · 3d (models)Elo1403
7thof 93Design Arena · asciiart (models)Elo1321
7thof 68Design Arena · mobileapps (agents)Elo1265
7thof 35Furniture assembly — Epoch AImean_score (max)70
8thof 132Ale bench — Epoch AIPerformance (high)2143.2
8thof 197Lmca — Epoch AIScore65.46
8thof 142Mystery game puzzles — Epoch AImean_score (max)58
8thof 306OTIS Mock AIME 2024-2025mean_score (max)100
9thof 82Cursorbench — Epoch AIScore (max)51.8
9thof 154Design Arena · dataviz (models)Elo1344
9thof 162Design Arena · gamedev (models)Elo1373
9thof 14Frontiermath erdos — Epoch AImean_score (max)0
10thof 260Critpt — Epoch AIAccuracy (xhigh)31.143
10thof 78Frontiermath tier 4 v2 — Epoch AImean_score (max)87.805
10thof 56Gdp pdf — Epoch AIGDP.pdf score (high)0.296
12thof 163Design Arena · codecategories (models)Elo1333
14thof 114Design Arena · svg (models)Elo1296
16thof 298ARC-AGI-2 (Semi-Private)Score (%) (max)90
16thof 290Arc agi 2 — Epoch AIScore (max)90
16thof 86Artificial Analysis · Intelligence IndexArtificial Analysis Intelligence Index50
16thof 157Design Arena · uicomponent (models)Elo1333
16thof 169Design Arena · website (models)Elo1308
17thof 298ARC-AGI-1 (Semi-Private)Score (%) (max)97.5
17thof 309Arc agi — Epoch AIScore (max)97.5
17thof 165LMArena · VisionScore (Elo) (max)1286
22ndof 154Chess puzzles — Epoch AImean_score (max)48
29thof 71Vending bench 2 — Epoch AIScore5421.557

About

Claude Fable 5.1 — a text model from Anthropic, sold by 13 companies from $10 in and $50 out per million tokens, placed 1st of 163 on Artificial Analysis · Coding Index.

It takes text, images and files and returns text, with a context window of 1,000,000 tokens. It was published in September 2026, trained on material up to June 2026. Its sellers say it can reason step by step and call a tool. The catalogue files it under reasoning, code and agents. Thirteen companies sell it. The cheapest is $10 in and $50 out per million tokens at Databricks. Beside the standard rate there are batch, separately routed and regional lanes. It has been measured on 57 boards, and stands best at 1st of 163 on Artificial Analysis · Coding Index.

Every current figure

Maker
Anthropic
Register
model
Takes
text + image + file
Returns
text
Context
1,000,000 tokens
Longest answer
128,000 tokens
Published
September 2026
Knowledge to
June 2026
Licence
not read
Sellers
13
Price
$10 in and $50 out per million tokens — Databricks
Boards
57
Best place
1st of 163 — Artificial Analysis · Coding Index

Known as 2 names

anthropic/claude-fable-5.1vertex/claude-fable-5.1