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title: Claude Fable 5 and Claude Mythos 5 | daily.dev
description: Anthropic has released Claude Fable 5, built on the same weights as the restricted Mythos model but with built-in safety classifiers that reroute high-risk...
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og:description: Anthropic has released Claude Fable 5, built on the same weights as the restricted Mythos model but with built-in safety classifiers that reroute high-risk...
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# Claude Fable 5 and Claude Mythos 5

**[Md. Shafin Ahmed](https://daily.dev/sources/u8ir8dacsyjsphydqqtq9)** · [@mdshafinahmed](https://daily.dev/mdshafinahmed) · 2 min read · 3 upvotes · 2 comments

## Summary

Anthropic has released Claude Fable 5, built on the same weights as the restricted Mythos model but with built-in safety classifiers that reroute high-risk queries to Claude Opus 4.8 (affecting under 5% of sessions). Benchmark highlights include 80.3% on SWE-Bench Pro vs GPT-5.5's 58.6%, and 29.3% on FrontierCode Diamond vs 5.7%. Real-world use cases include Stripe migrating a 50-million-line Ruby codebase in a single day. The restricted Mythos 5 autonomously ran genomics research, trained a custom ML model across 138 species, and outperformed a published Science paper model while being 100× smaller. Pricing is $10/1M input and $50/1M output, free on Pro/Max/Team plans until June 22. A new 30-day data retention policy now applies to all users including enterprise customers with prior zero-retention agreements.

## Content

Anthropic just released Claude Fable 5 — their most powerful model ever made publicly available. Here's what you need to know:

🔬 What it is:

Fable 5 runs on the same underlying weights as Mythos — the model that shocked the cybersecurity world in April. The difference? Built-in safety classifiers that reroute high-risk queries (cyber, biology, chemistry) to Claude Opus 4.8 automatically. Less than 5% of sessions are affected.

📊 Benchmark highlights (vs GPT-5.5):

→ SWE-Bench Pro: 80.3% vs 58.6%

→ FrontierCode Diamond: 29.3% vs 5.7%

→ CursorBench: 72.9% — 8pts above previous best

→ Frontier physics research: matched 4 days of GPT-5.5 work in 36 hours, using ⅓ the reasoning tokens

🏗️ Real-world proof:

Stripe used it to migrate a 50-million-line Ruby codebase in a single day — a job that would take a full engineering team over two months.

🧬 The science angle is underrated:

Mythos 5 (the restricted version for vetted partners) autonomously ran genomics research over a week, trained a custom ML model across 138 animal species, and outperformed a recently published model in Science — while being 100× smaller.

⚠️ Two things worth knowing before you deploy:

1. Safety filters are deliberately broad — some benign security tasks may get rerouted
2. New 30-day data retention policy applies to ALL users, including enterprise customers with previous zero-retention agreements (not for training, but for safety monitoring)

💰 Pricing: $10/1M input · $50/1M output

Free on Pro/Max/Team plans until June 22, then usage credits required.

This isn't just a faster model. It's the first AI that genuinely improves the longer it runs — designed for hours or days of autonomous work, not just single exchanges.

The capability bar just moved. Is your team ready to use it — and use it responsibly?

🔗 Full announcement: anthropic.com/news/claude-fable-5-mythos-5

#AI #Anthropic #ClaudeFable5 #LLM #SoftwareEngineering #AISafety #TechNews #FutureOfWork #MachineLearning

## Community discussion

Top comments from developers on daily.dev.

**@mdshafinahmed** · 1 upvotes

> I think this will be most out breaking model of Claude AI.

---

Tags: [#llm](https://daily.dev/tags/llm), [#anthropic](https://daily.dev/tags/anthropic), [#ai-coding](https://daily.dev/tags/ai-coding), [#ai-safety](https://daily.dev/tags/ai-safety)

[View this post on daily.dev](https://daily.dev/posts/claude-fable-5-and-claude-mythos-5-t3o5ecdo5)

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