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claude-fable-5 API pricing & access

claude-fable-5 API pricing: $10 per 1M tokens. claude-fable-5. Supports text, image input and text output. Listed specifications follow p…

claude-fable-5 API access

claude-fable-5. Supports text, image input and text output. Listed specifications follow public vendor documentation. Available features and limits depend on the selected serving channel.

Compare supported API endpoints and capabilities, then access claude-fable-5 through the unified API gateway.

Category
text
Context length
1000000 tokens
Maximum output
128000 tokens
Supported APIs
Anthropic Messages API, OpenAI Chat Completions API
API endpoints
POST /v1/messages, POST /v1/chat/completions
Input modalities
text, image
Output modalities
text
Capabilities
vision, reasoning

claude-fable-5 API pricing

Base input price
$10 per 1M tokens
Base output price
$50 per 1M tokens

Base prices are shown in USD before group-specific adjustments. Open the live pricing page for current access-group prices.

About claude-fable-5

claude-fable-5 is an earlier Anthropic Fable model with text and image input, text output and always-on adaptive thinking. Its current page marks it as an active legacy model; existing long-running agent workflows can retain it as an evaluation baseline.

Evaluate Fable 5.1 for an upgrade using completed tasks, tool behavior and observed latency. Fable and the separately offered, organization-verified Mythos model do not confer interchangeable access rights.

Official reference, checked 2026-10-14.

Use cases and prompting

  1. Specify the goal, intermediate deliverables and stopping conditions for a long task.
  2. Limit tool permissions and define when failures should halt execution; validate in a test environment.
  3. Keep existing thinking and tool-call cases to check response structure and termination during migration.
  4. Compare the same test cases with claude-fable-5-1; check request and response formats in the API documentation.

How to call claude-fable-5

claude-fable-5 is served through tbuy's unified gateway. Existing OpenAI or Anthropic SDK code keeps working: point base_url at https://modelsok.com and use your tbuy API key.

curl (OpenAI-compatible)

curl https://modelsok.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "claude-fable-5", "messages": [{"role": "user", "content": "Hello"}]}'

Python (openai SDK)

from openai import OpenAI

client = OpenAI(base_url="https://modelsok.com/v1", api_key="YOUR_API_KEY")
response = client.chat.completions.create(
    model="claude-fable-5",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

Python (anthropic SDK)

from anthropic import Anthropic

client = Anthropic(base_url="https://modelsok.com", api_key="YOUR_API_KEY")
message = client.messages.create(
    model="claude-fable-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
)
print(message.content[0].text)

Frequently asked questions about claude-fable-5

What is claude-fable-5?

claude-fable-5. Supports text, image input and text output. Listed specifications follow public vendor documentation. Available features and limits depend on the selected serving channel.

How do I call claude-fable-5?

Create an API key with access to claude-fable-5, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.

How is claude-fable-5 priced?

Pricing depends on the selected provider group and the model billing unit. Refer to the current input, output, request, or media prices in the pricing section.

What is the context window of claude-fable-5?

The model catalog lists a context window of 1000000 tokens. Check the selected endpoint for request limits.

What is the maximum output of claude-fable-5?

The model catalog lists a maximum output of 128000 tokens. Your request settings may set a lower limit.

How should I evaluate claude-fable-5 for my project?

Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.

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