Claude Fable 5.1
AnthropicKey claude-fable-5-1Also reported as anthropic/claude-fable-5-1, router_client:claude/claude-fable-5-1, claude/claude-fable-5-1, auto/claude-fable-5-1, cursor/claude-fable-5-1, devin/claude-fable-5-1, teamclaude/claude-fable-5-1, cc/claude-fable-5-1, anthropic/claude-fable-5.1, my anthropic sub/claude-fable-5-1, hohoai/hohoai/claude-fable-5-1, router_client:unknown/claude-fable-5-1, pve-claude-drtechmes/claude-fable-5-1, eai/claude-fable-5-1, s6o/claude-fable-5-1
- Rank
- #7
- by active users
- Active users
- 362
- Down 162 from 524 active users in the previous 30 days. vs previous 30 days
- Adoption
- 38%
- of 961 accounts
- Tokens
- 474.8B
- cache included
- Est. cost
- $656K
- at public list prices
- First seen
- Jul 11, 2026
- in any submission
Oct 14 – Nov 12, 2026 (UTC)961 accounts100% of tokens from an identified modelData through Nov 12, 2026, 06:48 UTCHow we count
Daily active users
Distinct accounts that used this model on each UTC day.
8 active users on Nov 12, 2026
Show daily values
| Date (UTC) | Active users | Tokens |
|---|---|---|
| Oct 14, 2026 | 161 | 22.4B |
| Oct 15, 2026 | 156 | 21.9B |
| Oct 16, 2026 | 136 | 22.3B |
| Oct 17, 2026 | 93 | 17B |
| Oct 18, 2026 | 106 | 14.6B |
| Oct 19, 2026 | 150 | 19.7B |
| Oct 20, 2026 | 150 | 22.3B |
| Oct 21, 2026 | 146 | 26.1B |
| Oct 22, 2026 | 142 | 26.7B |
| Oct 23, 2026 | 129 | 28.3B |
| Oct 24, 2026 | 98 | 19.7B |
| Oct 25, 2026 | 91 | 11.7B |
| Oct 26, 2026 | 105 | 15.8B |
| Oct 27, 2026 | 112 | 15.1B |
| Oct 28, 2026 | 123 | 15.2B |
| Oct 29, 2026 | 121 | 14.5B |
| Oct 30, 2026 | 102 | 13.9B |
| Oct 31, 2026 | 84 | 13.3B |
| Nov 1, 2026 | 80 | 9.9B |
| Nov 2, 2026 | 116 | 11.8B |
| Nov 3, 2026 | 113 | 17.5B |
| Nov 4, 2026 | 105 | 25.4B |
| Nov 5, 2026 | 100 | 13.2B |
| Nov 6, 2026 | 84 | 13.3B |
| Nov 7, 2026 | 67 | 10.5B |
| Nov 8, 2026 | 64 | 9.8B |
| Nov 9, 2026 | 81 | 15.4B |
| Nov 10, 2026 | 62 | 5.9B |
| Nov 11, 2026 | 29 | 1B |
| Nov 12, 2026 | 8 | 408.4M |
Token mix
How the 474.8B tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.
- Input0.9%
- Output0.5%
- Cache read93%
- Cache write6.1%
- Reasoning<0.1%
Agents that carry Claude Fable 5.1
Each agent's share of this model's tokens, and how many accounts used the model through it.
Claude Code74% of this model's tokens335active users
Senpi (OmO Native)13% of this model's tokens36active users
Pi4.6% of this model's tokens7active users
Oh My Pi4.2% of this model's tokens22active users
Hermes Agent4.0% of this model's tokens3active users
Junie0.2% of this model's tokens1active users
Droid<0.1% of this model's tokens1active users
Aside<0.1% of this model's tokens3active users
Codex CLI<0.1% of this model's tokens3active users
Gajae Code<0.1% of this model's tokens2active users
OpenCode<0.1% of this model's tokens4active users
Prime Agent<0.1% of this model's tokens1active users
ZCode<0.1% of this model's tokens1active users
Synthetic<0.1% of this model's tokens1active users
Cherry Studio<0.1% of this model's tokens2active users
Benchmarks
The best result for Claude Fable 5.1 in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark. Agent rows also show Tokscale usage through that agent, side by side with the score. Usage does not explain the score.
- Epoch Capabilities IndexOverall · Epoch AI167.0
Epoch Capabilities Index: 167.0
- Model
- Claude Fable 5.1
- Listed as
- Claude Fable 5.1
- Conditions
- Not reported
- Interval
- 164.2–170.1
- Unit
- ECI
- Model released
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #7 of 158 matched modelsNo conditions reportedModel released Sep 1, 2026Source: epoch.ai (opens in a new tab) - Terminal-Bench 4.1Agentic coding · Terminal-Bench57.6%
Terminal-Bench 4.1: 57.6%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1
- Conditions
- XHigh · Claude Code
- Interval
- 54.3–60.9%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Best of 5 reported results for this model.
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
Rank #5 of 23 matched modelsXHigh · Claude CodePublished Nov 3, 2026Source: tbench.ai (opens in a new tab)
Tokscale usage: Claude Code carried 74% of Claude Fable 5.1 tokens in the last 30 days (335 active users).Show 4 more results with other run conditionsHide the other results
- Listed as Fable 5.157.3%
Terminal-Bench 4.1: 57.3%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1
- Conditions
- Max · Claude Code
- Interval
- 53.4–61.1%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
- Listed as Fable 5.154.9%
Terminal-Bench 4.1: 54.9%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1
- Conditions
- High · Claude Code
- Interval
- 51.4–58.3%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
- Listed as Fable 5.153.9%
Terminal-Bench 4.1: 53.9%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1
- Conditions
- Medium · Claude Code
- Interval
- 50.5–57.3%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
- Listed as Fable 5.143.3%
Terminal-Bench 4.1: 43.3%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1
- Conditions
- Low · Claude Code
- Interval
- 39.7–46.9%
- Unit
- % resolved
- Published
- Nov 3, 2026
- Retrieved
- Nov 12, 2026
Source · Terminal-Bench 4.1 official leaderboard, tbench.ai
- CursorBenchAgentic coding · Cursor, collected by Epoch AI51.8%
CursorBench: 51.8%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1 Max
- Conditions
- Max
- Unit
- score
- Model released
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Best of 5 reported results for this model.
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Show 4 more results with other run conditionsHide the other results
- Listed as Fable 5.1 Extra High51.6%
CursorBench: 51.6%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1 Extra High
- Conditions
- XHigh
- Unit
- score
- Model released
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as Fable 5.1 High49.2%
CursorBench: 49.2%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1 High
- Conditions
- High
- Unit
- score
- Model released
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as Fable 5.1 Medium46.8%
CursorBench: 46.8%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1 Medium
- Conditions
- Medium
- Unit
- score
- Model released
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- Listed as Fable 5.1 Low45.1%
CursorBench: 45.1%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1 Low
- Conditions
- Low
- Unit
- score
- Model released
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · CursorBench results by Cursor, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierSWEAgentic coding · FrontierSWE, collected by Epoch AI56.3%
FrontierSWE: 56.3%
- Model
- Claude Fable 5.1
- Listed as
- Claude Fable 5.1
- Conditions
- Max · proximus
- Unit
- mean@5
- Model released
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · FrontierSWE results, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Rank #6 of 23 matched modelsMax · proximusModel released Sep 1, 2026Source: frontierswe.com (opens in a new tab) - WebDev ArenaWeb development · LMArena1,743
WebDev Arena: 1,743
- Model
- Claude Fable 5.1
- Listed as
- Claude Fable 5.1 (Max)
- Conditions
- Max
- Interval
- 1734–1752
- Unit
- Arena score
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
- Agent ArenaAgents · LMArena+0.14
Agent Arena: +0.14
- Model
- Claude Fable 5.1
- Listed as
- Claude Fable 5.1 (Max)
- Conditions
- Max · Arena Agent Mode
- Interval
- 0.12 to 0.16
- Unit
- net improvement
- Published
- Oct 19, 2026
- Retrieved
- Oct 21, 2026
Source · LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset on Hugging Face), CC BY 4.0
Rank #3 of 48 matched modelsMax · Arena Agent ModePublished Oct 19, 2026Source: huggingface.co (opens in a new tab) - Humanity's Last ExamReasoning · Center for AI Safety and Scale AI, collected by Epoch AI46.5%
Humanity's Last Exam: 46.5%
- Model
- Claude Fable 5.1
- Listed as
- Fable 5.1 (xhigh)
- Conditions
- XHigh
- Unit
- % correct
- Model released
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · Humanity's Last Exam results, collected by Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
- FrontierMath Tiers 1–3 (v2)Reasoning · Epoch AI90.2%
FrontierMath Tiers 1–3 (v2): 90.2%
- Model
- Claude Fable 5.1
- Listed as
- claude-fable-5-1_max
- Conditions
- Max
- Unit
- % solved
- Run date
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Near its ceiling: the top score is 95.1%, and Epoch AI estimates the reachable maximum at 95%. Differences between top models are small.
- SimpleQA VerifiedKnowledge · Epoch AI70.8%
SimpleQA Verified: 70.8%
- Model
- Claude Fable 5.1
- Listed as
- claude-fable-5-1_max
- Conditions
- Max
- Unit
- % correct
- Run date
- Sep 1, 2026
- Retrieved
- Nov 12, 2026
Source · Epoch AI, ‘Capabilities & benchmarking’, epoch.ai/benchmarks (CC BY 4.0)
Pricing
List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. Anthropic is the lab's own API and the reference price for the estimates below.
Price at real agent usageEstimate at list prices
What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.
- At this model's mix
- $1.34
- Est. per 1M tokens
93% cache reads - At the community mix
- $0.81
- Est. per 1M tokens
96% cache reads - 3:1 input/output blend
- $20
- Per 1M tokens at list prices
No cache
Cache reads were 93% of Claude Fable 5.1 tokens in the last 30 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.
Assumptions
- Anthropic list prices per 1M tokens: input $10, output $50, cache read $0.25, cache write $12.50.
- This model's mix is its own input, output, cache and reasoning tokens in the last 30 days.
- The community mix is the tokens of every identified model in the last 30 days.
- This is an estimate at list prices, not what anyone paid.
- Reasoning tokens are priced as output.
- Long-context tiers, batch pricing and discounts are not applied.
- Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
List prices by provider
- AnthropicReference
claude-fable-5-1$10 input per 1M tokens$50 output per 1M tokens$0.25 cache read per 1M tokens$12.50 cache write per 1M tokens1M tokens of context - Amazon Bedrock
anthropic.claude-fable-5-1$10 input per 1M tokens$50 output per 1M tokens$0.25 cache read per 1M tokens$12.50 cache write per 1M tokens1M tokens of context - Vertex
claude-fable-5-1@default$10 input per 1M tokens$50 output per 1M tokens$0.25 cache read per 1M tokens$12.50 cache write per 1M tokens1M tokens of context - Vertex (Anthropic)
claude-fable-5-1@default$10 input per 1M tokens$50 output per 1M tokens$0.25 cache read per 1M tokens$12.50 cache write per 1M tokens1M tokens of context
Show 3 more providersShow fewer providers
- Azure
claude-fable-5-1$10 input per 1M tokens$50 output per 1M tokens$0.25 cache read per 1M tokens$12.50 cache write per 1M tokens1M tokens of context - OpenRouter
anthropic/claude-fable-5.1$10 input per 1M tokens$50 output per 1M tokens$0.25 cache read per 1M tokens$12.50 cache write per 1M tokens1M tokens of context - Vercel AI Gateway
anthropic/claude-fable-5.1$10 input per 1M tokens$50 output per 1M tokens$0.25 cache read per 1M tokens$12.50 cache write per 1M tokens1M tokens of context
Specs
From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.
- Context window
- 1M tokens
- Max output
- 128K tokens
- Input
- Text, Image, PDF
- Output
- Text
- Knowledge cutoff
- Jun 2026
- Release date
- Sep 1, 2026
- Open weights
- No
- Reasoning
- Yes
- Tool calling
- Yes
Top public profiles
Public profiles that used Claude Fable 5.1 most in this period, by tokens. Hidden accounts are never listed.
- 1
Soju06@Soju06141.7Btokens$272.9Kest. cost28active days$272.9K est. cost · 28 active days
- 2
YeonGyu-Kim@code-yeongyu24.7Btokens$27.7Kest. cost27active days$27.7K est. cost · 27 active days
- 3
LJM@lee98www18.7Btokens$7.9Kest. cost25active days$7.9K est. cost · 25 active days
- 4
G Man@genx7up12.7Btokens$13.9Kest. cost27active days$13.9K est. cost · 27 active days
- 5
cairnskald@cairnskald12.1Btokens$27.9Kest. cost28active days$27.9K est. cost · 28 active days
- 6
Sunghyun Cho@anaclumos11.1Btokens$13.3Kest. cost20active days$13.3K est. cost · 20 active days
- 7
Henrik@henrigkroine8.6Btokens$16.3Kest. cost18active days$16.3K est. cost · 18 active days
- 8
Jonathannkayy@Jonathannkayy8.2Btokens$5.3Kest. cost29active days$5.3K est. cost · 29 active days
- 9
NickHW@HyunWoo-Nick7.6Btokens$5.1Kest. cost18active days$5.1K est. cost · 18 active days
- 10
dletterio1@dletterio17.3Btokens$6.6Kest. cost20active days$6.6K est. cost · 20 active days
More from Anthropic
Other Anthropic models in the same period, by active users.
- Claude Opus 5.574% adoption713active users
- Claude Sonnet 5.558% adoption557active users
- Claude Haiku 5.550% adoption479active users
- Claude Opus 4.823% adoption222active users
- Claude Fable 5.220% adoption192active users
- Claude Opus 517% adoption164active users
Sources and attribution
Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.