Anthropic's Mythos-class model (successor to Fable 5), its most capable for coding, knowledge work and long-horizon agentic tasks; with cheaper cache reads.
Context window
1M
tokens
Max output
128,000
tokens
Release date
1 September 2026
Access:APIHostedDeployment:☁ Cloud
Overview
Access & deployment
APIHosted
Cloud
Weights: Closed
Key parameters
📏 Context: 1M
✓ Tools
📥 Input: text, image, documents
Technical specification
Context window
1M
tokens
Max output tokens
128,000
tokens per response
Knowledge cutoff
1 Jun 2026
Knowledge boundary
Features:✓ Tool use
Modalities
⬇ Input
textimagedocuments
⬆ Output
textcode
Capabilities and applications
Native model capabilities
Reasoning
The model's ability to reason logically and solve complex problems.
Category: reasoning
Advanced reasoning
The ability to perform multi-step, structured reasoning: analysing problems, planning steps, and drawing conclusions from hypotheses. Reasoning-first models (e.g. GPT-5.1 Thinking) dedicate a portion of inference to chains of thought before responding.
Category: reasoning
Multi-step reasoning
Carrying out multi-step chains of reasoning across long, complex tasks.
Category: reasoning
Extended thinking mode
A reasoning-model variant with a larger inference budget: more thinking cycles, higher answer precision at the cost of response time. Choice between 'standard' and 'extended' thinking is left to the user (e.g. the selector in GPT-5.2 Pro).
Category: reasoning
Long context
Support for large context windows — tens to hundreds of thousands (or millions) of input tokens. Enables analysis of entire codebases, long documents, and many parallel conversations without losing earlier information. GPT-5.1 supports 400,000 tokens.
Category: language
Coding
Generating, analysing and modifying code in many programming languages. Covers writing functions, debugging, refactoring, code review, and creating tests. Measured by benchmarks such as HumanEval and SWE-bench.
Category: coding
Agentic capability
The model's ability to autonomously plan and execute multi-step tasks by sequentially using tools, maintaining context, and adapting to intermediate results.
Category: planning
Computer use
The model's ability to operate a computer interface by interpreting screenshots and generating actions such as clicks, typing, and navigating applications.
Category: planning
Function Calling
Category: planning
Structured output
Producing data in structured formats such as JSON.
Category: structured_generation
Image understanding
Analysing and interpreting the content of images.
Category: vision
Chart understanding
Reading and interpreting charts, tables and diagrams.
Category: vision
OCR
Recognising text within images and documents.
Category: vision
Multilingual
Competence in many natural languages (from a few to over a hundred): understanding, generation, translation, and code-switching within a single conversation. Frontier models support a wide range of languages with comparable quality.
Category: language
Planning
Forming and executing action plans for complex tasks.
Category: planning
Benchmark results
5 benchmarks
Terminal-Bench-Science 0.1
accuracy
52.6%%
📄 Anthropic — ogłoszenie Claude Fable 5.1 i Mythos 5.1
Fable 5.1 score (52.6%) — up from Fable 5 (24.7%), Opus 5 (29.0%) and GPT-5.6 Sol (22.4%).
OSWorld 2.0 (strict)
success rate
41.7%%
📄 Anthropic — ogłoszenie Claude Fable 5.1 i Mythos 5.1
Computer-use benchmark (strict). Fable 5.1 41.7% vs Fable 5 36.1% and Opus 5 39.6%.
OSWorld 2.0 (partial)
success rate
77.9%%
📄 Anthropic — ogłoszenie Claude Fable 5.1 i Mythos 5.1
Computer-use benchmark (partial). Fable 5.1 77.9% vs Fable 5 72.9% and Opus 5 75.4%.
Terminal-Bench 4.0
accuracy
55.8%%
📄 Anthropic — ogłoszenie Claude Fable 5.1 i Mythos 5.1
Terminal agentic tasks. Fable 5.1 55.8% vs Fable 5 42.0% (Mythos 5.1 60.9%).
CursorBench 3.2.0
accuracy
73.4%%
📄 Anthropic — ogłoszenie Claude Fable 5.1 i Mythos 5.1
Coding benchmark (Cursor). Fable 5.1 73.4% vs Fable 5 70.5%.
Pricing
Technical architecture
Core Architecture
Model Form
Training Techniques
Deployment and security
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