Anthropic
Claude Fable 5.1
Frontier coding and agentic model by Anthropic with state-of-the-art SWE-Bench Verified performance.
Intelligence
88.4 #26
Top 3% tier
Output Speed
85 t/s
TTFT 350 ms · ITL 11.8 ms/tok
Blended price (3:1)
$6 /1M
In $3/M · Out $15/M
Context
500K
≈ 1,250 A4 pages · max out 32,768
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Claude Fable 5.1
Claude Mythos Preview (#1)
Average (68)
Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.
Strengths & Trade-offs
Where it wins
- Frontier coding at GA — top SWE-bench Verified tier
- Mythos-class capability with publicly documented mitigations
- 1M context with strong agentic and long-context scores
Trade-offs to watch
- $10/$50 premium-tier pricing
- Some cybersecurity queries are down-routed to Opus 4.8
- Closed weights — API only
Killer Use Cases
Production agentic coding
Mythos-tier coding available to every developer through the standard API.
Knowledge work automation
Long-horizon document, analysis and research tasks.
Secure code review
High-recall review of large diffs with safeguarded output.
Developer Quickstart & API
Set
ANTHROPIC_API_KEY first — get an API keycurl https://api.anthropic.com/v1/messages \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-H "content-type: application/json" \
-d '{
"model": "claude-fable-5-1",
"max_tokens": 1024,
"messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
}'import anthropic
client = anthropic.Anthropic() # reads ANTHROPIC_API_KEY
msg = client.messages.create(
model="claude-fable-5-1",
max_tokens=1024,
messages=[{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}],
)
print(msg.content[0].text)const res = await fetch("https://api.anthropic.com/v1/messages", {
method: "POST",
headers: {
"x-api-key": process.env.ANTHROPIC_API_KEY,
"anthropic-version": "2023-06-01",
"content-type": "application/json",
},
body: JSON.stringify({
model: "claude-fable-5-1",
max_tokens: 1024,
messages: [{ role: "user", content: "Refactor this function for O(n) time and explain the change." }],
}),
});
console.log((await res.json()).content[0].text);Official Resources & Links
API deployment
Compare hosts & latency
Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Scores by Source
Category Scores
Benchmark Results
Head-to-head Live Matchups
Live Specs & Architecture
Under the hood
Mythos-class transformer — GA configuration
- Fable 5.1 refresh — same Mythos-class backbone with updated post-training
- 500K context with effort tiers low → xhigh
- Published joint system card with Mythos 5.1 (September 2026)
Release date
Aug 15, 2026
Architecture
Mythos-class transformer — GA configuration
Parameters
Not disclosed
License
Proprietary
Context Window
500,000 tokens
Max Output
32,768 tokens
Modalities
text + image
Cache Pricing
read $0.3 · write $3.75 /1M
Reasoning
Effort levels
Input Price
$3/M
Output Price
$15/M
Output Speed
85 t/s
Time to First Token
350 ms
Data Updated
Sep 2, 2026
Estimated monthly bill
Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...
Cite & embed
GitHub Markdown badge
Loading badge markdown...BibTeX
@misc{llmpodium2026claudefable51,
title = {Benchmark Analysis and Intelligence Evaluation of Claude Fable 5.1},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/claude-fable-5-1}
}Embed Score Badge
Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.
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