Claude Fable 5

Claude Fable 5 is Anthropic's current public high-end model for coding, analysis, and long-horizon workflows, with built-in safety behavior and API-level controls for cost-aware production use.

Platform: Replicate

Reasoning AICoding AssistantAutonomous WorkflowsSafety-aware AI

0 runs

Input: $10 per million tokens; Output: $50 per million tokens

Commercial

🚀Function Overview

A high-capability language model for long-form coding, complex analysis, and long-horizon tasks with practical safety fallback behavior.

Key Features

Large context and high output support for extended coding and agent tasks
Safety-aware classification and refusal behavior with escalation behavior for uncertain outputs
Mythos-class capabilities under a release-safe, generally available posture
Multimodal input support for vision-assisted coding and review tasks
Use-case fit for long-horizon and planning-heavy AI workflows

Use Cases

•Complex coding and software engineering assistance
•Long-horizon agentic workflows
•Document-heavy analysis and iterative reasoning tasks
•Vision-aware explanation and code-review prompts
•Production-facing copilots where safety boundaries matter

⚙️Input Parameters

prompt

string

The prompt to send to the model

image

string

Optional input image; priced by image token rules

system_prompt

string

System prompt for role and policy controls

max_tokens

integer

Maximum number of output tokens to generate

effort

string

Controls reasoning effort for adaptive, high-depth tasks

max_image_resolution

number

Maximum image resolution in megapixels; reduces token/cost and latency impact

💡Usage Examples

Example 1

Input Parameters

{
  "prompt": "Compare three options for refactoring a legacy API layer and propose the safest rollout plan.",
  "system_prompt": "You are a reliable software architect. Prioritize safety and backward compatibility.",
  "effort": "high",
  "max_tokens": 4096,
  "max_image_resolution": 0.5
}

Output Results

I would evaluate the three options by balancing blast radius, rollback path, and production risk.

First, I would classify the change set by coupling level and user impact.

Then I would apply a staged rollout: smoke tests, contract tests, canary deployment, and monitoring gates.

Option A offers speed but the highest breaking-risk; Option B reduces regression risk with moderate engineering effort; Option C is safest but slower.

Recommended rollout order: Option B with explicit rollback scripts and a compatibility smoke check at each step.

Quick Actions

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Technical Specifications

Hardware Type
Run Count: 0
Commercial Use: Supported
Pricing: Input: $10 per million tokens; Output: $50 per million tokens
Platform: Replicate

Related Keywords

Reasoning ModelCoding AssistantLong-horizon WorkflowAutonomous DevelopmentAnthropic APIModel Safety ControlsMultimodal Claude Model

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