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Anthropic: Claude Fable 5

2 providers live
anthropic/claude-fable-5
→
  • 2 live providers
  • 100% uptime
  • 4.29 s first token
  • 278 tok/s output
  • 25% off

Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token context window. It is suited for long-running, complex, and asynchronous tasks that previously required frequent human check-ins. It is particularly strong at end-to-end work that would otherwise take a person hours, days, or weeks - taking on problems that are long-running, ambiguous, or highly multi-step. It executes well-scoped tasks with few mistakes, automatically self-correcting through verification loops, and ships with robust safeguards.

Context
1M
tokens
Max output
128K
tokens
Input
$10.00 $7.50
per million tokens, 25% off
Output
$50.00 $37.50
per million tokens, 25% off

Providers

Ranked by price and speed. Requests go to the best healthy provider, then fail over down the list.Benchmarks
Live providers of Claude Fable 5, in the router's order
Who answers nowInput per 1MFirst token
llm.buzz25% offpicked$10.00 $7.505.14 s
Anthropic$10.004.29 s

llm.buzz answers now: lowest price.

First token is the 24-hour median. If the pick fails, the next one answers at its own price.

#ProviderInputOutputCache readLatencyThroughputUptime (3d)
1
llm.buzzAuto25% offNon-EU
Data policy not declared
$10.00 $7.50$50.00 $37.50$1.00 $0.755.14 s112 tok/s97.2%
2
AnthropicNon-EU
Data policy not declared
$10.00$50.00$1.004.29 s278 tok/s100%
Want to serve this model?Become a provider

Price history

No price changes since Oct 22, 2026. The history shows prices before discounts.

  • Anthropic$10.00 in, $50.00 out

Performance

Last 24 hours, from llm.buzz's test requests

Throughput (tok/s)

  • llm.buzz112 tok/s
  • Anthropic278 tok/s
Data table
ProviderFrom (UTC)p50p90p99
llm.buzzOct 26, 06:00112 tok/s112 tok/s112 tok/s
llm.buzzOct 26, 10:00193 tok/s193 tok/s193 tok/s
llm.buzzOct 26, 20:0093 tok/s93 tok/s93 tok/s
llm.buzzOct 27, 01:0093 tok/s93 tok/s93 tok/s
llm.buzzLast 24 hours112 tok/s93 tok/s93 tok/s
AnthropicOct 26, 06:00193 tok/s193 tok/s193 tok/s
AnthropicOct 26, 11:00278 tok/s278 tok/s278 tok/s
AnthropicOct 26, 16:00193 tok/s193 tok/s193 tok/s
AnthropicOct 26, 21:00278 tok/s278 tok/s278 tok/s
AnthropicOct 27, 01:00334 tok/s334 tok/s334 tok/s
AnthropicLast 24 hours278 tok/s193 tok/s193 tok/s

Latency (time to first token)

  • llm.buzz5.14 s
  • Anthropic4.29 s
Data table
ProviderFrom (UTC)p50p90p99
llm.buzzOct 26, 06:005.14 s5.14 s5.14 s
llm.buzzOct 26, 10:006.17 s6.17 s6.17 s
llm.buzzOct 26, 20:007.41 s7.41 s7.41 s
llm.buzzOct 27, 01:004.29 s4.29 s4.29 s
llm.buzzLast 24 hours5.14 s7.41 s7.41 s
AnthropicOct 26, 06:003.57 s3.57 s3.57 s
AnthropicOct 26, 11:004.29 s4.29 s4.29 s
AnthropicOct 26, 16:004.29 s4.29 s4.29 s
AnthropicOct 26, 21:004.29 s4.29 s4.29 s
AnthropicOct 27, 01:004.29 s4.29 s4.29 s
AnthropicLast 24 hours4.29 s4.29 s4.29 s

Uptime

Last 72 hours, by hour
Best provider 100%
This model
llm.buzz
Anthropic
  • Up: 95% or more served
  • Degraded: 85% to 95%
  • Down: below 85%
  • No data
  • From llm.buzz's test requests

Questions

How much does Anthropic: Claude Fable 5 cost?

Anthropic: Claude Fable 5 costs $7.50 per million input tokens and $37.50 per million output tokens at llm.buzz, the provider requests go to first, with cache reads at $0.75 per million tokens. These prices are 25% off until 2026-11-06 00:00 UTC. Each provider sets its own price, and you pay the price of the provider that answered.

Do providers train on my prompts?

Each provider declares it, and the table above shows every declaration. You can limit a request to providers that keep nothing, or to providers in the EU.

Can I serve Anthropic: Claude Fable 5 myself?

Yes. Apply as a provider, add your endpoint and list this model at your price. It goes live once the automated check passes.

Similar models

Call Anthropic: Claude Fable 5 with one keyEach request pays the price of the provider that answered it.