Anthropic Claude Fable 5 — Mythos but Safe, with Controversial Terms

By some measures, Opus 4.8, barely two weeks old, was already the leading model in the world. But now, 34 days after the SpaceXai deal and 63 days after the original Mythos announcement*, we have a Mythos-class model (at least 2x size of Opus) available to everyone (in coinciding with Claude Tokyo). It is a feat of incredible engineering (and commitment to access) to make these research models GA, and the benchmarks are great… with asterisks. Here they are on yesterday’s brand new, out of distribution, FrontierCode Diamond, going from 13.4% to 29.3%:

tweet

The blog and the system card contain most of the authoritative information, but don’t miss the youtube videos showing it playing Factorio, Pokemon (unlike Claude Plays Pokemon, this is just using vision, no complex harness as we covered in our pod), EDM visualization (never having head music before), 3D CAD editor creation and printing and more from their main intro video.

API pricing is also fantastic, at roughly 2x Opus.

The asterisks come because Fable is released with two controversial changes:

No ZDR: “We will require 30-day retention for all traffic on Mythos-class models, on both first- and third-party surfaces. We won’t use this data to train new Claude models, or for any non-safety-related purpose, and we’ve instituted new privacy protections including logging all human access to the data and ensuring its deletion after 30 days in almost all cases ...” (see full policy)

RSI suppression: “In light of the ability of recent models to accelerate their own development, we’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design). Using Claude to develop competing models already violates our Terms of Service, but enforcing this restriction through our safeguards avoids accelerating the actors most willing to violate these terms.

> Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT). These interventions will not affect the vast majority of coding work. We estimate they will impact ~0.03% of traffic, concentrated in fewer than 0.1% of organizations”.

The vast majority of users will not be affected by these limitations, but the open AI community is understandably upset, as you will see below.

You can find more of their recommendations on usage in Diane Penn’s Tokyo talk, which we have clipped below.

*(and 1 week-1 day after both Anthropic and OpenAI filed their S-1’s ahead of SpaceX’s IPO next week…)

AI News for 6/8/2026-6/9/2026. We checked 12 subreddits, 544 Twitters and no further Discords. AINews’ website lets you search all past issues. As a reminder, AINews is now a section of Latent Space. You can opt in/out of email frequencies!

AI Twitter Recap

Top Story: Anthropic Claude Fable 5 and Mythos 5 release

What happened

Anthropic released two versions of its next major model family: Claude Fable 5 for general availability and Claude Mythos 5 for restricted access.

Anthropic officially announced Claude Fable 5 as its “first generally available Mythos-class model,” saying it exceeds any model it has previously made broadly available and is state-of-the-art on nearly all tested benchmarks @claudeai, @claudeai

Anthropic said Fable 5 is the same underlying model as Mythos 5 with added safeguards, and that some cyber/bio/chemistry/distillation-related prompts may be routed to Claude Opus 4.8 instead @ClaudeDevs, @scaling01

Anthropic stated that for a “narrow range” of potentially harmful topics, queries transparently fall back to Opus 4.8, and claimed 95%+ of sessions never see one according to early user-facing messaging @claudeai, @mikeyk

Anthropic developer messaging said fallback is available server-side and via SDK middleware in Python, TypeScript, Go, Java, and C# @ClaudeDevs

Pricing for both Fable 5 and Mythos 5 was reported as $10 / million input tokens and $50 / million output tokens; cache pricing was later reported by third-party evaluators as $12.50 / million cache writes and $1 / million cache reads @scaling01, @ArtificialAnlys

Fable 5 kept Anthropic’s 1M-token context window according to Artificial Analysis @ArtificialAnlys

Anthropic put Fable 5 into Pro, Max, Team, and seat-based Enterprise plans until June 22, then said it would require usage credits due to capacity constraints, with plans to restore broader subscription access later @ClaudeDevs, @scaling01, @ArtificialAnlys, @kimmonismus

Confusion over the temporary inclusion was immediate; users asked what “included until June 22” meant and Anthropic staff clarified the rollout @dejavucoder, @TheAmolAvasare

Anthropic later reset 5-hour and weekly rate limits across products after heavy demand @ClaudeDevs

Official claims and third-party benchmark data

Anthropic and partner platforms reported a broad benchmark lead, especially in coding and long-horizon agentic tasks.

Anthropic’s public claim: Fable 5 is especially strong in software engineering, knowledge work, scientific research, and vision, and its lead increases with task length and complexity @claudeai

Cursor said Fable 5 set a new CursorBench SOTA at 72.9%, 8 points above the previous best @cursor_ai

Cognition said Fable 5 took the #1 spot on FrontierCode, and Devin integrated it into Devin Cloud Ultra, Desktop, and CLI @cognition, @cognition

Cline reported Fable 5 at 88.0% on Terminal-Bench 2.1, beating GPT-5.5 by 4.6 points @cline

Artificial Analysis placed Fable 5 #1 on its Intelligence Index at 64.9, roughly 5 points ahead of GPT-5.5, and said Anthropic occupied the top two spots @ArtificialAnlys

Artificial Analysis also reported:

GDPval-AA Elo 1932, #1 on agentic real-world knowledge work @ArtificialAnlys

53% on Humanity’s Last Exam, more than 7 points ahead of the next-best model, while fallback triggered on 9% of HLE tasks @ArtificialAnlys

~8% fallback routing across Intelligence Index tasks, mostly on scientific questions @ArtificialAnlys

Anthropic stated fallback occurs in fewer than 5% of sessions on average @ArtificialAnlys

Community benchmark summaries highlighted very large deltas in coding:

SWE-Bench Pro: Fable 5 80.3% vs GPT-5.5 58.6% @Yuchenj_UW

FrontierCode Diamond: Mythos 5 30.9% vs second-best 13.4% @scaling01

Anthropic ECI 161.29 for Mythos 5 @scaling01

Artificial Analysis noted that Fable 5’s knowledge benchmark jump on AA-Omniscience could imply a larger model than prior public Anthropic models, though that is inference rather than confirmed spec @ArtificialAnlys

Product behavior, usage profile, and deployment details

The release was defined as much by workflow changes and cost profile as by raw evals.

Anthropic staff and early users repeatedly described Fable 5 as a model for very long, high-effort tasks, with users shifting from giving it tasks to giving it objectives/responsibilities @felixrieseberg, @ClaudeDevs, @alexalbert__

Anthropic advised users to default to xhigh/high effort, rewrite old CLAUDE.md instructions, and let the model use more judgment @alexalbert__

Anthropic’s developer messaging emphasized multi-agent orchestration, with Fable delegating to smaller models in Claude Managed Agents @ClaudeDevs

Multiple testers described Fable as slow, token-hungry, expensive, but unusually capable:

Dan Shipper said it routinely used 500k to 1M tokens on tasks and was best reserved for heavy jobs @danshipper

Simon Willison called it “slow, expensive and capable” @simonw

Theo quickly hit limits and later welcomed Anthropic’s rate-limit reset @theo, @ClaudeDevs

Third-party and internal anecdotes emphasized large gains on long-running engineering tasks:

Ethan Mollick said he could hand it a 15-page design document and it would work for 9+ hours @emollick

Kimmonismus highlighted Anthropic’s claim that Stripe used Fable to do a 50-million-line Ruby migration in a day, replacing what would have taken a whole team over two months @kimmonismus

Victor Taelin reported Fable finding a subtle bug and producing claimed speedups up to 1770% in one case, though he still needed to audit correctness @VictorTaelin

Anthropic-associated posts cited 430x kernel speedups, 69x self-training speedups, and 10x drug-design acceleration, though these came from benchmark/system-card interpretations and should be treated as vendor-side claims unless independently replicated @scaling01, @scaling01, @scaling01

Ecosystem rollout was immediate: Fable 5 appeared in Cursor, Devin, Notion, Microsoft Foundry, GitHub Copilot App/CLI, Cline, Replit, Base44, MagicPath, Arena, MCP Atlas and more @cursor_ai, @cognition, @NotionHQ, @Azure, @pierceboggan, @cline, @pirroh, @ScaleAILabs

Safety architecture and the main controversy

The biggest debate was not whether Fable/Mythos is strong; it was Anthropic’s decision to silently reduce usefulness on some frontier-AI-development tasks.

Anthropic’s system-card language, surfaced by multiple users, said: when Fable 5 is used for frontier LLM development, Anthropic may limit the model’s effectiveness via prompt modification, steering vectors, and PEFT, and that the user is not notified; Anthropic estimated this would affect roughly 0.03% of traffic @Hangsiin, @kimmonismus

Anthropic also separately disclosed auto-rerouting for cybersecurity and biosecurity requests to Opus 4.8 @ClaudeDevs

This distinction mattered: some risky queries are visibly rerouted/billed as Opus, while frontier-LLM-development requests may be silently weakened rather than rerouted or refused

Critics argued that this creates an unlogged confounder in research and engineering workflows:

“silent handicaps should not be a thing in a paid product” @nrehiew_

“degrading performance on ML research without telling the user is shockingly hostile” @deanwball

Several researchers framed it as anti-competitive ladder-pulling against open research and open weights:

“labs starting to pull up the ladders” @natolambert

“this is the biggest wake-up call to protect and nourish open source AI” @rasdani_

“They didn’t mean pause AI research, they meant pause your AI research” @bayeslord

“original thinkers can’t be an underclass” @marksaroufim

“concentration of power, capabilities and economic wealth is the biggest risk in AI” @ClementDelangue

Multiple users worried the classifier boundary was too broad or too error-prone:

one user said “the word cancer is flagged as a biosecurity risk” @DeryaTR_

another said Fable wouldn’t answer “What does the heart do?” @Yuchenj_UW

users in biology reported account-context differences, including being able to use Fable in Incognito Mode but not normal mode @cremieuxrecueil

Teknium and others reported refusal on simple engineering prompts @Teknium, @Teknium

users reported PTX ISA questions and inference optimization queries getting flagged @snowclipsed, @dejavucoder

Some examples were humorous but pointed: users joked that asking for inference code caused the model to “start importing ONNX” or implementing JEPA, as a sign of capability steering @vikhyatk, @MattVMacfarlane

Facts vs. opinions

Facts / directly supported by release materials or benchmark posts

Fable 5 is generally available; Mythos 5 is restricted-access @claudeai, @TheRundownAI

Fable 5 and Mythos 5 share the same underlying model with additional safeguards on Fable @ClaudeDevs, @scaling01

Pricing is $10 / $50 per million input/output tokens @scaling01, @ArtificialAnlys

Fable retains 1M context @ArtificialAnlys

Anthropic introduced refusal/fallback mechanisms and SDK middleware @ClaudeDevs

Anthropic disclosed silent interventions for frontier LLM developme

[truncated for AI cost control]