Fable
7 storiesFable is an AI model that appears in recent coverage mainly in comparisons with other frontier models. Anthropic said its Opus 5.5 beat the larger Fable model on many benchmarks and cut output pricing to $20 per million tokens from $25, while Anthropic's decision to retain Fable usage logs for 30 days led Palantir, Nvidia and Booz Allen Hamilton to pull back on sensitive work. Producer Edward Saatchi also plans to use AI through his startup Fable to recreate the lost ending of Orson Welles's The Magnificent Ambersons.
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A Hacker News user reported that Claude Opus 5.5 seemed markedly worse with poor attention span over about half a day, across agents on very different projects. Commenters cited daily benchmark results suggesting the model has not degraded, and compared it with Fable 5.1 on reasoning and style.
British producer Edward Saatchi plans to use artificial intelligence to recreate the lost original ending of Orson Welles's The Magnificent Ambersons, which was altered by the studio. The project, driven by his AI filmmaking startup Fable, is both ambitious and controversial.
Anthropic released Opus 5.5, claiming new state-of-the-art coding and knowledge work performance, beating the larger Fable model on many benchmarks. Output pricing drops to $20 per million tokens from $25, with faster, less compute-intensive serving and clearer communication. Sonnet 5.5 and Haiku 5.5 are due in coming weeks.
The piece says AI firms’ promises not to train on customer data haven’t resolved trust issues: Anthropic’s decision to retain Fable usage logs for 30 days prompted Palantir, Nvidia and Booz Allen Hamilton to pull back on sensitive work.
Artificial Analysis added a private eval in Intelligence Index v4.3 replacing τ³; Astra had been scoring strongly and matched Fable, but community posts report DeepSeek V4.1 Flash took first on that eval; the index was changed twice in three days.
A Hacker News thread asks which default model people use. One user says they use Claude most, find Fable overkill and costly for their needs, and has made Opus 4.8 their go-to due to good value while avoiding Opus 5 for now.
A user pushed Qwen 3.8 27B (q4xl) locally with a PI agent to handle a large game design file, using ~120k context plus vision and MTP. The run read ~11M tokens and wrote ~3.2M tokens over about 12 hours, demonstrating local model capability for complex game design tasks.
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