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FlagshipAnthropic
Claude Fable 5
Claude Fable 5 is a flagship-tier model from Anthropic in its Fable family, accepting text and image input with a 1,000,000-token context window.
Context 1.0M
Tier Flagship
Knowledge Jan 2026
Tools Supported
Modalities text, image
Input from
$5.00 / 1M tokens
across 4 providers
API Pricing
Cheapest on Anthropic — 40% below avg| Provider | Input / 1M | Output / 1M | Cached / 1M |
|---|---|---|---|
| $5.00 | $25.00 | $0.500 | |
| $5.00 | $25.00 | $0.500 | |
| $10.00 | $50.00 | - | |
| $10.00 | $50.00 | $1.00 | |
| $10.00 | $50.00 | $1.00 | |
| $10.00 | $50.00 | $1.00 |
Prices updated daily. Last check: Sep 8, 2026
Claude Fable 5 pricing by provider
Input, output, and batch rates, plus alternatives, for one provider at a time.
Performance & Benchmarks
Source: Artificial Analysis →Intelligence
53.2 / 100
Coding
76.5 / 100
Output Speed
62.2 t/s
Latency (TTFT)
51.0s
Reasoning & Knowledge
- GPQA Diamond92.6%
- Humanity's Last Exam55.5%
Coding
- SciCode61.0%
Agentic & Tool Use
- Terminal-Bench Hard62.9%
- Terminal-Bench v2.184.6%
- τ²-bench98.5%
- τ-bench Banking38.1%
Instruction & Long Context
- IFBench63.5%
- Long-Context Reasoning82.3%
Benchmarks measured Sep 2026. Scores are independent evaluations, not vendor-reported.
Model Details
General
- Creator
- Anthropic
- Family
- Fable
- Tier
- Flagship
- Context Window
- 1.0M
- Knowledge Cutoff
- Jan 2026
- Modalities
- Text, Image
Capabilities
- Tool Calling
- Yes
- Open Source
- No
- Aliases
- claude-fable-5, Claude Fable 5, anthropic.claude-fable-5
Strengths & Limitations
Strengths
- 1,000,000-token context window, large enough for full document collections or large codebases in a single request
- Accepts image input alongside text, so screenshots, charts, and scanned pages can be processed without a separate vision model
- Tool calling is supported, enabling function-calling and agentic orchestration patterns
- Flagship tier within Anthropic's Fable family, the configuration aimed at the family's hardest tasks
- Knowledge cutoff of January 2026 per Anthropic's published metadata
- Third-party throughput and latency measurements are available from Artificial Analysis, giving an independent performance reference point
Limitations
- Measured time to first token of roughly 60 seconds (Artificial Analysis) makes it unsuitable for real-time chat or autocomplete UIs
- Output throughput of about 65.7 tokens/sec is moderate, so long generations take noticeable wall-clock time
- Flagship-tier models are generally the most expensive option in a family; lighter Fable variants may be more economical for simple tasks
- Filling the full 1M-token context has cost and latency consequences even when the window technically allows it
- We do not track published benchmark scores (reasoning, coding, math) for this model, so capability comparisons rely on vendor claims
Key Features
•1,000,000-token context window
•Text and image (vision) input
•Tool calling / function calling support
•Flagship tier of Anthropic's Fable family
•January 2026 knowledge cutoff
•Measured output speed of ~65.7 tokens/sec (Artificial Analysis)
•Multiple API aliases including claude-fable-5 and anthropic.claude-fable-5
About Claude Fable 5
Claude Fable 5 is a model from Anthropic, positioned at the flagship tier of the company's Fable family. As the flagship entry in that family, it is the configuration intended for the family's most demanding workloads rather than for cost-sensitive, high-volume tasks.
The model accepts both text and image input and exposes a 1,000,000-token context window, which is large enough to hold long document sets, extended conversation histories, or sizable code repositories in a single request without external chunking. Tool calling is supported, so the model can be wired into function-calling and agentic loops. Anthropic lists a knowledge cutoff of January 2026 for the model. Independent measurements from Artificial Analysis put output throughput at roughly 65.7 tokens per second, with a measured time to first token of about 60.4 seconds — a notably long latency to the first token, which suggests substantial upfront processing before generation begins.
In practice, a flagship model with a million-token window and image input tends to be applied to long-context analysis, multi-step agent workflows, and tasks that mix documents, screenshots, or diagrams with text instructions. The very high measured time to first token makes it a poor fit for interactive, latency-sensitive interfaces, and better suited to batch or background jobs where total completion time matters more than perceived responsiveness. Availability and pricing differ by provider — see the pricing table on this page.
Common Use Cases
Claude Fable 5 fits workloads where context size and input breadth matter more than response latency: analyzing large document sets or contract archives in one pass, reasoning over an entire codebase, summarizing long meeting or research corpora, and multi-step agent runs that accumulate long tool-call histories. Image input extends this to mixed-media jobs such as reviewing slide decks, invoices, technical diagrams, or UI screenshots alongside written instructions. Because the measured time to first token is around a minute, it is better matched to batch pipelines, scheduled analysis jobs, and background agents than to interactive assistants; for user-facing chat or streaming-dependent UX, a lower-latency model — including smaller variants if available — is usually the more practical choice.
Frequently Asked Questions
How much does Claude Fable 5 cost?
Pricing varies by provider and by pricing type — input versus output tokens, batch versus real-time, and any caching discounts a provider offers. Check the pricing table on this page for current rates across the providers we track.
What is Claude Fable 5 best used for?
Long-context analysis and agentic workflows. The 1,000,000-token window suits full-repository code review, large document collections, and extended agent histories, while image input covers mixed text-and-visual material such as slides, diagrams, and screenshots. It is best used where total job completion matters more than instant first response.
Is Claude Fable 5 fast enough for interactive applications?
Generally no. Artificial Analysis measured a time to first token of roughly 60 seconds and output throughput of about 65.7 tokens per second. That first-token latency is far too high for chat interfaces or code autocomplete, though it is acceptable for batch and background processing.
Can Claude Fable 5 process images?
Yes. Its confirmed modalities are text and image, so images can be supplied as input alongside text prompts. We do not have information on image generation or other output modalities.
Does Claude Fable 5 support tool calling?
Yes, tool calling is supported, which allows it to be used in function-calling setups and agent frameworks. Specific implementation details, such as parallel tool execution or structured output modes, depend on the provider's API surface.
How does Claude Fable 5 relate to other Fable models?
It sits at the flagship tier of Anthropic's Fable family, meaning it is the configuration positioned for the family's most demanding tasks rather than for high-volume, cost-sensitive work. If Anthropic offers smaller Fable variants, those would typically trade capability for lower cost and latency.