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Claude Fable 5

everyais/claude-fable-5

Claude Fable 5 (everyais/claude-fable-5) availability, capabilities, context limits, and public reference pricing on everyais.

Model family claudeInput Text · ImageOutput Text
Available now

Method

The page starts with current public catalog metadata and reference costs; operational metrics are added only when measured samples are available.

Source and update

GET /models/catalog

Updated

Model type
Chat
Released
2026-06-09
Context window
1.0M
Price unit
Per 1M tokens
Maximum output
128,000
Model reference price (USD)
Input $10 · Output $50 /1M
Cache reference price (USD)
Cache read $1 /1M · Cache write $12.5 /1M

Capabilities

  • Streaming
  • Tool use
  • Vision
  • JSON
  • Reasoning
  • parallel_tool_calls

Supported endpoints

  • /v1/chat/completions

Usage and availability trend

Daily tokensInputOutput
2K1K02026-08-252026-09-032026-08-25 · Requests 1 · Input 1,063 · Output 853 · Availability Insufficient sample2026-08-26 · Requests 0 · Input 0 · Output 0 · Availability Insufficient sample2026-08-27 · Requests 0 · Input 0 · Output 0 · Availability Insufficient sample2026-08-28 · Requests 0 · Input 0 · Output 0 · Availability Insufficient sample2026-08-29 · Requests 0 · Input 0 · Output 0 · Availability Insufficient sample2026-08-30 · Requests 0 · Input 0 · Output 0 · Availability Insufficient sample2026-08-31 · Requests 0 · Input 0 · Output 0 · Availability Insufficient sample2026-09-01 · Requests 0 · Input 0 · Output 0 · Availability Insufficient sample2026-09-02 · Requests 1 · Input 16 · Output 11 · Availability Insufficient sample2026-09-03 · Requests 1 · Input 13 · Output 8 · Availability Insufficient sample

Last 10 days · 2026-09-03 Input 13 · Output 8 tokens.

Daily availability (success rate %)

Insufficient sample — not enough requests to publish a success rate.

Code example

Use the OpenAI SDK by changing only base_url.

from openai import OpenAI

client = OpenAI(
    api_key="everyais_...",
    base_url="https://api.everyais.com/v1",
)

response = client.chat.completions.create(
    model="everyais/claude-fable-5",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)
Full API docs

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