← Back
FeaturedAIModels#Anthropic#Claude Fable 5#GPT-5.6 Sol#Kimi 3 - Moonshot AI#Compute Allocation#Subscription Pricing

Anthropic Backs Down: Claude Fable 5 Permanently Included in Subscription Plans

Simon Willison 博客(Atom)T2
14:0007/18, 02:00 PMCommunityRead the original ↗Export MD ↓

Score

75
Information gain8 ×0.3

提供了 Anthropic 订阅计划重大调整的明确决策和原因,对追踪AI定价策略的用户价值高。

Content quality7 ×0.2

观点清晰,包含了竞争背景和算力影响分析,但缺乏官方声明细节的引用。

Practical value9 ×0.2

直接帮助订阅用户了解新资费规则和积分变化,实用性强。

Timeliness10 ×0.15

发布时间与事件发生几乎同步,符合突发新闻的时效性要求。

Source reliability8 ×0.15

来源为知名技术博客 Simon Willison 的 Atom 频道,转载自官方推特,可信度高。

Base 83 × T2 Source weight ×0.9 = 75

Curation line 70Selected

Why selected

Highly timely, directly covers a key Anthropic product decision, but limited depth on compute impact analysis.

AI commentary

「This is a major policy reversal for Anthropic subscribers: what was thought to be the last week of Fable 5 access is now permanent, with extra credits thrown in. Anyone tracking AI pricing and compute allocation should read closely: it shows how competitive pressure reshapes even the largest players' calculus between profit and market share.」

Quick overview

Anthropic announced that starting July 20, Claude Fable 5 will be permanently included in Max and Team Premium subscription plans at 50% of limits. Pro and Team Standard users will still access Fable via usage credits and receive a one-time $100 credit. Previously, Anthropic had planned to make Fable 5 available exclusively via API pricing, but competition from GPT-5.6 Sol and Kimi 3 forced a change. The decision eases fears of a 'Fablepocalypse' but raises questions about whether Anthropic's compute reallocation might impact model training.

  • Anthropic reverses course: Claude Fable 5 will be included in Max and Team Premium plans at half limits, not just API.
  • Pro and Team Standard users receive a one-time $100 credit to continue using Fable 5 via usage credits.
  • Competitive pressure from GPT-5.6 Sol and Kimi 3 drove Anthropic's policy change.
  • Anthropic may need to divert training compute to serve Fable 5, raising concerns about future model progress.

Full text

Showing the source text; the full translation is being generated.

Claude make Fable 5 permanent

An update from the @claudeai account on Twitter:

Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits.

Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit.

As I was saying last week, the competition from GPT-5.6 Sol (and maybe to a lesser extent Kimi 3) made untenable Anthropic's plan to remove Fable 5 from their subscription accounts and make it available exclusively through API pricing.

Why pay $100 or $200/month for a subscription plan that doesn't include Anthropic's best model?

Their original plan was driven by concerns over compute capacity. I wonder if they'll have to dial back their training efforts in order to make more GPUs available to help serve the model.

A lot of people were losing sleep over trying to make the most of Fable 5 before subscriber access was withdrawn. It's nice not to have to worry about the Fablepocalypse any more.

Tags: ai, generative-ai, llms, anthropic, claude, llm-pricing, claude-mythos-fable

Other reports on this story

Related items

92
08:00OpenRouter:Announcements(RSS)T1RSS

FeaturedDeepSeek V4 Doubles Token Share on OpenRouter, Driven by Agentic Workloads

DeepSeek V4 在 OpenRouter 上的代币份额翻倍,智能体工作负载成主要驱动力

The rapid adoption of DeepSeek V4 signals a strong market preference for high-performance, low-cost inference models, especially as agentic use cases reshape AI deployment.

AIModels#DeepSeek#OpenRouter#V4 Flash
91

Five-dimension score

Information gain9 ×0.3

详细揭示了两个具体设置如何协同作用实现三倍性能提升,信息增量高。

Content quality8 ×0.2

来自OpenAI官方,数据明确,结构清晰,但缺少对比实验细节。

Practical value9 ×0.2

为AI工程师提供了可直接操作的性能调优方案,实用性强。

Timeliness10 ×0.15

消息刚发布,具有高度时效性。

Source reliability10 ×0.15

信源为OpenAI官方新闻,权威可靠。

Base 91 × T1 Source weight ×1 = 91

Curation line 60Selected

23:00OpenAI:News(RSS)T1RSS

FeaturedEnabling Two Settings Triples ARC-AGI-3 Benchmark Scores

启用两项设置使ARC-AGI-3基准测试分数提升三倍

This finding is crucial! It shows that model performance depends not only on training but also on inference-time configuration. For AI engineers and researchers, this is a must-know optimization direction. Teams deploying models on resource-constrained devices in particular could find a low-cost way to boost capabilities.

TechModels#ARC-AGI-3#GPT-5.6#OpenAI
91

Five-dimension score

Information gain9 ×0.3

首次公开GPT-5.6具体效率优化细节,此前仅有传闻。

Content quality8 ×0.2

内容简洁,关键指标明确,但缺乏详细技术文档支撑。

Practical value9 ×0.2

直接指导企业如何降低AI部署成本,具有商业参考价值。

Timeliness10 ×0.15

刚发布的官方新闻,时效性极强。

Source reliability10 ×0.15

来源为OpenAI官方博客,信源权威。

Base 91 × T1 Source weight ×1 = 91

Curation line 60Selected

08:00OpenAI:News(RSS)T1RSS

FeaturedGPT-5.6: Fusing Frontier Intelligence with Frontier Efficiency

GPT-5.6:前沿智能与前沿效率的融合

This news is worth watching as it marks a shift from pure parameter scaling to efficiency competition. For AI developers and business decision-makers, GPT-5.6 means higher performance at lower cost, especially for long-context or agentic tasks previously hindered by inference expenses. OpenAI's move may redefine what 'frontier' means.

AIModels#Agent Workflows#GPT-5.6#OpenAI
91

Five-dimension score

Information gain8 ×0.3

首次提出针对CPU优化的1M上下文模型,填补了边缘设备长文本推理的空白,信息增量显著。

Content quality9 ×0.2

技术细节清晰,提供了基准测试对比和架构解释,图文并茂,质量上乘。

Practical value10 ×0.2

直接降低长上下文应用的硬件成本,开源权重可立即部署,实用价值极高。

Timeliness10 ×0.15

当日发布的博客,且长上下文推理是当前AI热点,时效性满分。

Source reliability9 ×0.15

Hugging Face官方博客,作者为Liquid AI,属于第一方技术发布,可信度高。

Base 90.5 × T1 Source weight ×1 = 91

Curation line 60Selected

23:01Hugging Face:Blog(RSS)T1RSS

FeaturedLFM2.5-Encoders: New Models for Fast Long-Context Inference on CPU

LFM2.5-Encoder:面向CPU快速长上下文推理的新模型

This blog post catches my eye because it directly solves the pain point of running long-context LLMs on CPU. For teams or individual developers without high-end GPUs, the LFM2.5-Encoder series offers a ready-to-use open-source solution. Highly recommended for those working on RAG, document search, or code analysis—now a standard server can handle million-token documents.

AIModels#CPU Inference Optimization#LFM2.5-Encoder#Liquid AI
91

Five-dimension score

Information gain9 ×0.3

首次公开自动化红队系统的具体机制与实验发现,信息增量高。

Content quality8 ×0.2

来自官方,结构清晰,但未提供完整技术细节(如具体模型版本),扣1分。

Practical value9 ×0.2

对AI安全工程师、模型开发者和企业部署者直接指导作用,实用性极强。

Timeliness10 ×0.15

刚刚发布,是当前AI安全领域最前沿进展之一。

Source reliability10 ×0.15

信源为OpenAI官方新闻,权威且一手。

Base 91 × T1 Source weight ×1 = 91

Curation line 60Selected

18:00OpenAI:News(RSS)T1RSS

FeaturedGPT-Red: OpenAI Automates Red Teaming via Self-Play to Boost Model Robustness

GPT-Red:OpenAI通过自我对弈实现AI红队自动化,提升模型鲁棒性

GPT-Red marks a milestone from human to automated red-teaming—essential for safety engineers and alignment researchers. While reducing cost, it also raises ethical questions about automated attacks, worth pondering for everyone in AI governance.

AIModels#AI Safety Alignment#GPT-Red#OpenAI
91

Five-dimension score

Information gain9 ×0.3

这是首个针对AI模型生物安全的漏洞赏金计划,为行业提供了全新的安全评估视角。

Content quality9 ×0.2

官方来源,内容清晰,涵盖范围、奖励、准则等关键细节。

Practical value8 ×0.2

对AI安全研究员和生物安全专家有直接参与价值,但普通用户关联度较低。

Timeliness10 ×0.15

刚刚发布,完全符合新闻时效要求。

Source reliability10 ×0.15

OpenAI官方RSS和博客,信源权威可靠。

Base 91 × T1 Source weight ×1 = 91

Curation line 60Selected

18:00OpenAI:News(RSS)T1RSS

FeaturedOpenAI Launches GPT-5.5 Bio Bug Bounty Program

OpenAI推出GPT-5.5生物漏洞赏金计划

This program deserves attention as it pioneers the extension of AI bug bounty to biosecurity, offering a new research direction for the security community and a practical training ground for AI risk governance. It is particularly important for model safety researchers, biosecurity experts, and practitioners concerned about dual-use AI risks.

AIModels#Bio Bug Bounty#GPT-5.5#OpenAI
91

Five-dimension score

Information gain8 ×0.3

公布了vLLM新后端的具体架构设计与实测数据,对了解推理优化前沿有较高信息增量。

Content quality9 ×0.2

技术细节清晰,有定量性能对比,来源为官方博客,内容质量高。

Practical value10 ×0.2

直接降低LLM部署门槛与成本,对AI工程化落地具有极高实用价值。

Timeliness10 ×0.15

发布即时,属于最新技术动态,时效性满分。

Source reliability9 ×0.15

来源为Hugging Face官方博客,vLLM为开源权威项目,可信度高。

Base 90.5 × T1 Source weight ×1 = 91

Curation line 60Selected

08:00Hugging Face:Blog(RSS)T1RSS

FeaturedvLLM Introduces Native-Speed Transformers Modeling Backend for Enhanced Inference Performance

vLLM推出原生速度Transformers建模后端,大幅提升推理性能

This update is critical for AI engineering teams: eliminating format conversion speeds up model iteration, and 2-5x speedup directly reduces GPU costs. If you're building LLM online services or batch inference, this is practically a must-read technical update.

AIModels#Hugging Face#PagedAttention#Transformers
90

Five-dimension score

Information gain9 ×0.3

手语转文本是AI无障碍领域的新突破,提供了此前罕见的具体模型信息。

Content quality8 ×0.2

来源权威,内容清晰描述了模型功能、应用场景和开发理念。

Practical value9 ×0.2

对聋人群体、开发者和无障碍研究者具有直接参考与应用价值。

Timeliness9 ×0.15

刚刚发布的官方公告,时效性非常高。

Source reliability10 ×0.15

Google DeepMind官方博客,信源可信度极高。

Base 89.5 × T1 Source weight ×1 = 90

Curation line 60Selected

22:01Google DeepMind:Blog(RSS)T1RSS

FeaturedGoogle DeepMind Introduces SL2T, a Sign Language-to-Text Model for Deaf Users

Google DeepMind 发布手语转文本模型 SL2T,助力聋人用户

This news matters not only as a technical breakthrough but also as a sign that AI is beginning to address the needs of marginalized groups. For developers, the architecture and technical approach of SL2T merit deep study; for accessibility advocates, it's a key case for advancing industry standards.

AIModels#Google DeepMind#SL2T#Sign Language Recognition

Verify against the original source before citing