API Hop

Claude Fable 5 API: Pricing, Playground and Examples

Review Claude Fable 5 API pricing and Messages integration for research, code analysis and complex written work, with text examples and account-access checks.

Claude Fable 5 API pricing and billing

Official price

Input
$10.0000 /M
Output
$50.0000 /M
Cache input
$1.0000 /M
Cache write (5m)
$12.5000 /M
Cache write (1h)
$20.0000 /M

API Hop price Save 45%

Input
$5.5000 /M
Output
$27.5000 /M
Cache input
$0.5500 /M
Cache write (5m)
$6.8750 /M
Cache write (1h)
$11.0000 /M

Reference price - not independently verified. Check the publisher's current rates, billing units and applicable terms before comparing costs.

Claude Fable 5 online chat tool

Model settings

Advanced parameters
0 or more characters(0/No fixed limit)
No fixed character limit; the full request is subject to request-size and model-context limits. This is not a token count.
0 – 2
0 – 1
-2 – 2
-2 – 2

Conversation

How can I help you today?

Ready

Reset and start a new conversation?

This will clear the conversation and any unsent message, and restore default parameters.

Claude Fable 5 prompt examples

These are evaluation prompts for Claude Fable 5, not recorded model outputs. They analyze only supplied text; they do not execute code, inspect production systems or prove long-context performance. Check quoted evidence and acceptance criteria, then review response metadata and usage before production use.

Extract these synthetic records into JSON with fields id, owner, deadline and evidence: [R1] Issue 41: Ana owns the export fix; no deadline agreed. [R2] Issue 42: review due October 15; owner not assigned; year not stated. Use null for missing values and preserve partial dates as given. Quote the source in evidence. Do not invent a year or owner. Check each field against its record; this is a text-formatting task, not a database operation.

Use only this document sample: [P1] The export fix passed staging checks. [P2] A Friday release was proposed, not approved. [P3] Mei will review error messages on Tuesday. [P4] No owner is assigned to documentation. Return a table of claim, exact supporting quote, paragraph ID and uncertainty. Is production release approved? Who owns documentation? Mark missing facts unknown. Every quote must match the supplied sample; do not infer production success from staging. This small sample does not test maximum context length.

Review this fictional payment-webhook policy: every failed POST is retried three times, no idempotency key is stored, and the balance is debited before the response is sent. Identify duplicate-charge risks, propose minimal changes and three acceptance tests. Use only these facts; do not assume access to code, tools or production systems.

What is Claude Fable 5?

Claude Fable 5 model focus and core capabilities

Claude Fable 5 is Anthropic's general-use Mythos-class model for demanding reasoning and long-horizon work. Its capabilities cover software engineering, knowledge work, visual understanding, and scientific analysis; the Fable name does not make it a fiction-only model. Safety classifiers apply to sensitive requests, so its behavior should not be equated with unrestricted Mythos access.

Claude Fable 5 online tools and API on API Hop

API Hop provides an online text Playground, unified Chat Completions, and Claude Messages for Claude Fable 5. Test relevant tasks here before integrating the model into an application. Native vision, persistent file-based memory, and agentic demonstrations do not mean this text tool uploads files, remembers across sessions, or executes external actions.

Claude Fable 5 capabilities and domain strengths

Fable 5 is a candidate for work where code, documents, and decisions need to remain consistent across multiple steps. Give it a defined deliverable, relevant material, and clear boundaries rather than expecting the model name to establish what it can access or do.

Software engineering beyond isolated snippets

Use Claude Fable 5 to investigate a failure across related modules, review a proposed migration, or connect a feature specification to code and tests. Supply the relevant interfaces, logs, and existing behavior so the answer can distinguish a reproducible defect from an unsupported guess.

Ask for the smallest justified change, the affected callers, and checks that would falsify the proposed fix. A generated patch is still a proposal: this Playground cannot read your repository, run a terminal, or establish that tests passed.

Long-context reasoning and external memory boundaries

The native model has a one-million-token context window, creating room for substantial source material. For a design review, organize inputs by document or module and ask for requirement-to-evidence mappings, unresolved contradictions, and assumptions that need an owner's decision.

The length accepted by API Hop depends on the selected interface and upstream service. A native context window is not a promise of perfect recall or a permanent memory store; file-based memory in an agent requires your application to save, retrieve, and govern those notes.

Visual understanding for interface and document work

Fable 5's native visual capabilities support detailed technical images and interface analysis. A visual development workflow can connect what appears on screen to layout requirements, component behavior, and a checkable implementation plan.

This page provides text conversations without image, PDF, or video upload controls. Describe the layout and relevant values here, or first confirm the input format supported by another interface. A link pasted into text does not prove the model downloaded or inspected an image.

Complex analysis with explicit scope and safeguards

Use Fable 5 for analytical briefs that must reconcile multiple constraints: a technical option review, a research-method comparison, or a professional document assessment. Ask it to separate provided facts, interpretations, and open questions, and request a concise explanation rather than a reproduction of hidden reasoning.

Sensitive requests can be declined by the model's safeguards. For financial, legal, or scientific decisions, verify figures and conclusions against the original material and obtain appropriate professional review; an articulate analysis is not evidence that an outcome is correct or authorized.

How to evaluate Claude Fable 5 for your workload

Benchmark results are useful only with their task, tools, effort settings, and scoring conditions. For Fable 5, assess whether a result includes external execution or fallback behavior before translating it into expectations for a text request. This page does not promise a API Hop latency or success rate.

Suggested evaluation design; no measured results
Task inputChecksPass criteriaMetrics to record
A known cross-file defect or migration issue with expected behaviorReview the diagnosis, contract preservation, and proposed regression coverageThe root cause is addressed and relevant checks pass in the supplied environmentAccepted answers, regressions, corrections, duration, token usage

Evaluate difficult engineering tasks

Build a small set of known defects, cross-file changes, and migration questions. Score whether the answer locates the actual issue, preserves existing behavior, and proposes tests covering the failure, rather than rewarding a long explanation or a large patch.

Agentic coding evaluations may include repository access, tools, and repeated execution feedback. Use a comparable environment when evaluating an integrated agent; a single Playground response only evaluates the supplied text and cannot reproduce a tool-enabled benchmark.

Measure source fidelity in analytical work

For document analysis, include materials with known contradictions and missing information. Check attribution, retained quantities, constraint coverage, and whether the model keeps unresolved decisions open instead of silently choosing a convenient answer.

For an application using supported visual inputs, verify extracted values against the image and distinguish extraction errors from subsequent reasoning errors. Do not treat a vision score as evidence that this text Playground has inspected a chart or document.

Compare useful output, time, and actual usage

Keep prompts, material, output requirements, and grading rules consistent across runs. Record accepted answers, corrections, time to first useful text, total duration, and actual token usage; use the current account price rather than a static cost estimate.

Hard reasoning tasks can take longer, and conversation history or generous output allowances can increase usage. Include refusals and incomplete responses in your evaluation, and inspect the returned state before retrying rather than assuming every HTTP success contains a usable answer.

Claude Fable 5 compared with Claude, GPT, and Kimi models

Choose by the work you need to complete, not by a model name or an isolated leaderboard position. The following comparison defines useful tests for Fable 5 and related catalog models without assigning unsupported performance scores.

Task-based model comparison and validation criteria
TaskClaude Fable 5 evaluationOther candidatesValidation
Cross-file repairIdentify cause, affected callers, and minimal fixClaude Opus 5 / GPT-5.6 SolPassing tests and preserved behavior
Document synthesisTrack claims, contradictions, and open decisionsKimi K3 / Claude Opus 5Source fidelity and missing facts
Feature planningTranslate constraints into scope and acceptance checksClaude Sonnet 5 / GPT-5.6 SolCoverage without invented requirements
Iterative revisionMake a targeted change without drifting from the briefClaude Sonnet 5 / Kimi K3Retained facts and correction effort

When to prioritize testing Claude Fable 5

Prioritize a Fable 5 trial when a task combines difficult engineering or analysis with several dependent requirements. A migration review, ambiguous failure investigation, or conflicting-document brief gives a more informative test than a generic greeting.

Include simpler tasks in the comparison too: a complex model may not be the best fit for every step. Test against your required output and current prices, and keep external tools and refusal handling consistent so differences are meaningful.

Choose models by task on API Hop

Compare Claude Opus 5 and GPT-5.6 Sol for engineering or detailed reasoning, Kimi K3 for source-rich analysis, and Claude Sonnet 5 for iterative planning and revision. These are evaluation candidates, not claims that one model always wins the named task.

The shared Chat Completions format makes text comparisons easier, but native Messages and other protocols have different envelopes and parameters. Reuse your grading rubric while checking each model's supported interface, output controls, and current account price.

Why use Claude Fable 5 through API Hop?

Usage-based billing and model cost optimization

Charges follow current API Hop rates and actual usage. Top up on demand.

Unified AI models and data APIs, with multi-model access in one place

One API key connects multiple AI models and data services, reducing integration costs and letting you switch with one click. Business applications need both AI and data.

Call logs and application access controls, with clarity on every call

Every API call is recorded in your dashboard. Create separate API keys for different applications.

Evaluate outputs against your task

Use the documented model ID and supported parameters through API Hop. Evaluate outputs against your own acceptance criteria, then inspect usage records and response metadata before production use. A model name or example does not guarantee each result.

How to use Claude Fable 5 on API Hop

After creating an API key in the console, follow the documentation to get started with Claude Fable 5.

Prepare your account and test online

Sign in, confirm your balance, and create an API key.

Try it in the Playground

Explore the model's capabilities in the Playground to find the best way to use it.

Integrate Claude Fable 5 into your business

Follow our developer documentation to integrate Claude Fable 5 into your business.

Future model upgrades

To switch to a newer model, first confirm that its exact ID is returned by the model catalog for your API key. If it supports the same endpoint and request fields, update the model ID, then test response formats, streaming, output limits and billing before sending production traffic. For asynchronous image or video tasks, also verify job submission, status polling and result retrieval.

Claude Fable 5 API FAQ

Is Claude Fable 5 the same API model as Fable 5.1?

No. The API model name for Claude Fable 5 is claude-fable-5; the API model name for Claude Fable 5.1 is claude-fable-5-1. They are different models, so do not mix up their model parameters.

Why is thinking empty or the answer incomplete?

Native Fable 5 uses adaptive thinking by default and can omit thinking text. Ordinary requests do not need a thinking parameter, and empty thinking alone is not a failure. For an incomplete answer, check the completion state and output allowance, leaving enough room for thinking and final text.

How should I troubleshoot authentication, balance, or access errors?

Follow the API error documentation to diagnose the issue.

Can I use OpenAI Responses for Claude Fable 5?

OpenAI Responses is not supported. Claude has its own Claude Messages format; see the documentation for details.

Can I force a tool call or edit a native Messages conversation?

Native Fable 5 supports forced tool_choice types any or tool with adaptive thinking. Follow the documentation for the interface you use. Take care when replaying preserved thinking after editing earlier messages. Keep native assistant content blocks and their signatures intact during tool continuations.

Is conversation memory permanent?

No. The API does not automatically retain conversation context for subsequent requests. Manage the history yourself and include the required context in each request. Long-term memory must be implemented by your application.

Related text APIs