Claude Fable 5.1 — Specifications
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Developer | Anthropic |
|---|---|
| Type | Reasoning / agentic |
| Modality | Text, vision |
| Parameters | Undisclosed |
| Context window | 1M |
| Max output | 128K |
| License | Proprietary |
| Open weights | No |
| Released | 2026-09 |
| Input price | $10.00 /1M |
| Output price | $50.00 /1M |
| API providers | Anthropic API, AWS, Google Cloud, Microsoft Azure |
Benchmarks
| Anthropic-reported | Terminal-Bench 4.0 55.8%; GDPval-AA v2 1853 Elo; OSWorld 2.0 (partial) 77.9%; Humanity's Last Exam 60.9% (no tools), 65.0% (with tools); CursorBench 3.2.0 73.4%; AutomationBench 31.4%. Cache reads $0.25 per 1M tokens. |
|---|
What is Claude Fable 5.1?
Claude Fable 5.1 is Anthropic’s most capable generally available model, released on 1 September 2026 as an update to Claude Fable 5. According to Anthropic, it is aimed at demanding reasoning and long-running agentic work: coding, multistep research, and document, spreadsheet and slide tasks. Claude Mythos 5.1 is the same model with different safeguards, offered only to organisations in Anthropic’s verification programmes.
API pricing is the same as Fable 5: $10 per million input tokens and $50 per million output tokens. Cache reads fell 75% to $0.25 per million, which Anthropic estimates makes typical workloads about 25% cheaper. It has a 1M-token context window and up to 128K output tokens, and runs on the Claude API as claude-fable-5-1 and on AWS, Google Cloud and Microsoft Azure.
For most work Anthropic now recommends starting with the cheaper Claude Opus 5.5 ($4 / $20) and moving to Fable 5.1 only when that falls short. Launch details are in our Fable 5.1 release story, and the AI API cost calculator compares monthly costs.
Claude Fable 5.1 pricing: API cost per 1M tokens
| Input (per 1M tokens) | $10.00 |
|---|---|
| Output (per 1M tokens) | $50.00 |
| Output/input ratio | 5× |
| Blended (4:1 in:out) | $18.00 per 1M tokens |
What Claude Fable 5.1 costs per month
Real monthly spend at a 4:1 input-to-output mix — the ratio a typical chat or RAG workload actually produces.
| Workload | Tokens / month | Cost / month |
|---|---|---|
| Side project | 1M in / 0.25M out | $23 |
| Small team | 20M in / 5M out | $450 |
| Production | 200M in / 50M out | $4,500 |
Run your own numbers in the AI API cost calculator.
Cheaper alternatives to Claude Fable 5.1
| Model | Blended $/1M | You save |
|---|---|---|
| Mistral 7B open | $0.0220 | 100% cheaper |
| Llama 3.1 8B open | $0.0220 | 100% cheaper |
| Mistral NeMo 12B open | $0.0240 | 100% cheaper |
Frequently asked questions
How much does Claude Fable 5.1 cost per 1M tokens?
Claude Fable 5.1 costs $10.00 per 1M input tokens and $50.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $18.00 per 1M tokens.
How much does Claude Fable 5.1 cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $450 on Claude Fable 5.1. A side project (1M in / 0.25M out) costs roughly $22.50.
What is a cheaper alternative to Claude Fable 5.1?
Mistral 7B is the strongest cheaper option in our database at $0.0220 per 1M blended — about 100% less than Claude Fable 5.1. It is also open-weight, so self-hosting is an option.
Can I run Claude Fable 5.1 locally?
No. Claude Fable 5.1 is a closed, API-only model — the weights are not released, so it cannot be self-hosted.
Why does Claude Fable 5.1 charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. Claude Fable 5.1 charges 5× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
See every Claude model priced side by side: Claude API pricing.
Prices are the published list rates for the model's primary API and are reviewed as providers change them. Volume, batch and cached-input discounts are not included. Compare every model side by side in the AI models database or the LLM leaderboard.