Anthropic just dropped Claude Fable 5.1 and Mythos 5.1 — a big jump in long-horizon agentic work, with prompt-cache reads now 4x cheaper and the model burning far fewer tokens to do the same job. The timing is the story: it landed right as OpenAI announced its plans for Astra, the first model it says crosses "Critical" cybersecurity capability. I put Fable 5.1 to work immediately — a fully-voiced Tarkov-style extraction game with an auto mode, and a replica of Stanford’s generative-agents "LLM Village" — each built in roughly 10–15 minutes.
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Check out my video on OpenAI’s rogue agent and the Hugging Face hack:
SOURCES:
Anthropic — Introducing Claude Fable 5.1 and Claude Mythos 5.1:
https://www.anthropic.com/claude-fable-and-mythos-5-1
Anthropic docs — What’s new in Claude Fable 5.1 (effort settings & tips):
https://platform.claude.com/docs/en/models/fable-5-1/whats-new-fable-5-1
OpenAI — Path to Astra: critical capabilities and frontier safeguards:
https://openai.com/index/path-to-astra/
CNBC — OpenAI says Astra is its first model to cross "Critical" cybersecurity capability:
https://www.cnbc.com/2026/09/01/open-ai-astra-cyber-model.html
Stanford — Generative Agents: Interactive Simulacra of Human Behavior (the original "LLM Village" paper):
https://arxiv.org/abs/2304.03442
CHAPTERS:
00:00 Fable 5.1 and Mythos 5.1 are here
00:25 The "price cut" — cache discount, fewer tokens
01:04 A preemptive strike at OpenAI’s Astra
01:45 Ethan Mollick’s Deep Watch and long-horizon judgment
02:05 I built a Tarkov-style game in 10 minutes
02:45 Replicating Stanford’s LLM Village
04:10 Tarkov 2.0 — procedural graphics, Russian voice lines
05:03 First impressions: speed, cost, taste
05:20 Readability: Fable 5.1 vs 5.0
06:15 Safeguards: fewer false refusals
06:44 Anthropic’s tips — try low effort
07:02 CursorBench numbers and 4x cheaper cache reads
07:41 Will this take the wind out of Astra’s sails?
#anthropic #claude #ai
