Claude Fable 5.1
Claude Fable 5.1 (anthropic/claude-fable-5.1) is Anthropic’s most capable widely released model and the successor to Fable 5: agentic coding, long-running agentic workflows and knowledge work. Besides the OpenAI-compatible POST /v1/chat/completions, the model is available through the Anthropic-protocol POST /v1/messages — it works in Claude Code and the Anthropic SDK directly.
Parameters and capabilities
Section titled “Parameters and capabilities”| Capability | Value |
|---|---|
model |
anthropic/claude-fable-5.1 (or short claude-fable-5.1) |
| Image input | Yes — image_url with a data: URL in the last message |
| File input | Yes — PDF, DOCX, TXT, CSV, XLSX, PPTX, up to 5 per request |
| Reasoning | reasoning_effort: low, medium, high, xhigh, max; disabling is not supported — reasoning is built into the model |
| Context cache read | 27.00 ₽ ($0.30) per 1M tokens |
| Context cache write | 1348.60 ₽ ($15) per 1M tokens |
| Context / output | 1,000,000 tokens / up to 128,000 |
A cache read on Fable 5.1 costs one fortieth of the input price (27.00 ₽ vs 1078.90 ₽) — noticeably cheaper than the Claude-family average; a write is ×1.25. Reasoning is billed as output tokens and consumes the max_tokens budget — see Context caching for details.
Examples
Section titled “Examples”A request with a reasoning depth
Section titled “A request with a reasoning depth”from openai import OpenAI
client = OpenAI(base_url="https://api.mixen.ai/v1", api_key="mxn-...")
resp = client.chat.completions.create( model="anthropic/claude-fable-5.1", messages=[{"role": "user", "content": "Refactor this FastAPI service: split the monolith into modules and justify the boundaries"}], reasoning_effort="high",)print(resp.choices[0].message.content)curl https://api.mixen.ai/v1/chat/completions \ -H "Authorization: Bearer $MIXEN_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "anthropic/claude-fable-5.1", "messages": [{"role": "user", "content": "Refactor this FastAPI service: split the monolith into modules and justify the boundaries"}], "reasoning_effort": "high" }'Streaming in Python
Section titled “Streaming in Python”stream = client.chat.completions.create( model="anthropic/claude-fable-5.1", messages=[{"role": "user", "content": "Plan a zero-downtime database migration: steps, risks, rollbacks"}], stream=True, stream_options={"include_usage": True},)for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True)Anthropic SDK
Section titled “Anthropic SDK”The same key and balance work via POST /v1/messages. The base URL has no /v1 suffix: the SDK appends it to the path itself, unlike the OpenAI SDK.
from anthropic import AsyncAnthropic
client = AsyncAnthropic( base_url="https://api.mixen.ai", api_key="mxn-...", # the x-api-key header is supported)msg = await client.messages.create( model="anthropic/claude-fable-5.1", max_tokens=2048, messages=[{"role": "user", "content": "Hi!"}],)print(msg.content[0].text)In Claude Code the model takes the top slot via ANTHROPIC_DEFAULT_OPUS_MODEL — see the Claude Code guide.
Per 1M tokens: input — 1078.90 ₽ ($12), output — 5394.40 ₽ ($60). Context cache: read — 27.00 ₽ ($0.30), write — 1348.60 ₽ ($15). Showcase prices follow the exchange rate — check current values in the catalog.
Strengths and limits
Section titled “Strengths and limits”- Agentic coding, long-running agentic workflows and knowledge work are the model’s profile per Anthropic; especially strong at long code refactors, front-end and visual code generation, finance and analysis tasks.
- More concise than Fable 5 in plans and summaries; Anthropic recommends it as a direct upgrade from Fable 5 and alongside Opus 5 on reasoning-heavy tasks.
- Reasoning is always on: depth is controlled by
reasoning_effortup toxhighandmax; theoffvalue is not supported by the model. - Claude Code and the Anthropic SDK connect directly — tool use, streaming,
count_tokensandcache_controlwork. - Prompt caching: a cache read is one fortieth of the input price (a Claude-family record), the main saving on long sessions.
- Reasoning consumes
max_tokens; up to 150,000 characters are taken from each file, no OCR. - Output at 5394.40 ₽ per 1M tokens is the top tier; for high-volume routine Claude Haiku 4.5 is cheaper — 107.90 ₽ input / 539.40 ₽ output.
All models — in the catalog. General text workflow — the chat guide.