The Models Trying to Fill the Fable Gap
Episode
29 min
Read time
2 min
Topics
Fundraising & VC, Design & UX, Artificial Intelligence
AI-Generated Summary
Key Takeaways
- ✓Model routing over brute force: Harvey's experiment with Fireworks demonstrates that pairing an open-weight GLM 5.1 worker model with a closed Opus 4.7 advisor — rather than using Opus exclusively — reduced costs significantly while actually improving performance. Smart per-task routing is now a measurable competitive advantage over defaulting to the most expensive frontier model.
- ✓GLM 5.2 cost arbitrage: ZAI's GLM 5.2 ranks first on BridgeBench and Reasoning benchmarks, beating Fable five at one-tenth the cost and 300 tokens per second throughput. For design tasks specifically, Hassan from Together found GLM costs 6¢ versus Opus at 49¢ — over six times cheaper — with outputs that are visually indistinguishable.
- ✓OpenRouter Fusion compound architecture: OpenRouter's Fusion API fans prompts out to a panel of models in parallel, each with web search and bash tools, then uses a judge model to synthesize responses. Internal benchmarks on 100 hard research tasks show panels of budget models can surpass individual frontier models at substantially lower cost per query.
- ✓Open-source as access insurance: The Fable shutdown reveals that building mission-critical workflows on closed frontier models carries government-imposed access risk. Running open-weight models on local hardware eliminates kill-switch exposure entirely. Microsoft is already preparing a locally hosted DeepSeek v4 fine-tune to power Copilot for enterprise customers within weeks.
- ✓Cursor Composer 2.5 cost-performance ratio: Composer 2.5, built on a Kimi model foundation and post-trained for coding, scores within five percentage points of Fable on coding benchmarks at roughly one-twelfth the price — $1 versus $12 per comparable task. However, updated agentic coding benchmarks from Artificial Analysis place it closer to open Chinese models than to GPT-4.5 or Opus 4.7.
What It Covers
The banning of Anthropic's Claude Fable five model triggers a global scramble for alternatives, as enterprises and governments reassess AI dependency on US frontier models. G7 leaders clash over access, while open-source Chinese models like GLM 5.2 and compound routing systems emerge as cost-competitive substitutes.
Key Questions Answered
- •Model routing over brute force: Harvey's experiment with Fireworks demonstrates that pairing an open-weight GLM 5.1 worker model with a closed Opus 4.7 advisor — rather than using Opus exclusively — reduced costs significantly while actually improving performance. Smart per-task routing is now a measurable competitive advantage over defaulting to the most expensive frontier model.
- •GLM 5.2 cost arbitrage: ZAI's GLM 5.2 ranks first on BridgeBench and Reasoning benchmarks, beating Fable five at one-tenth the cost and 300 tokens per second throughput. For design tasks specifically, Hassan from Together found GLM costs 6¢ versus Opus at 49¢ — over six times cheaper — with outputs that are visually indistinguishable.
- •OpenRouter Fusion compound architecture: OpenRouter's Fusion API fans prompts out to a panel of models in parallel, each with web search and bash tools, then uses a judge model to synthesize responses. Internal benchmarks on 100 hard research tasks show panels of budget models can surpass individual frontier models at substantially lower cost per query.
- •Open-source as access insurance: The Fable shutdown reveals that building mission-critical workflows on closed frontier models carries government-imposed access risk. Running open-weight models on local hardware eliminates kill-switch exposure entirely. Microsoft is already preparing a locally hosted DeepSeek v4 fine-tune to power Copilot for enterprise customers within weeks.
- •Cursor Composer 2.5 cost-performance ratio: Composer 2.5, built on a Kimi model foundation and post-trained for coding, scores within five percentage points of Fable on coding benchmarks at roughly one-twelfth the price — $1 versus $12 per comparable task. However, updated agentic coding benchmarks from Artificial Analysis place it closer to open Chinese models than to GPT-4.5 or Opus 4.7.
Notable Moment
In a striking policy contradiction, the US government banned Fable five globally citing national security, while Microsoft simultaneously prepared to fine-tune a Chinese open-source model and deploy it inside the productivity stack used by virtually every major American enterprise running Microsoft 365.
Episode Transcript
Today on the AI Daily Brief, the models trying to replace Fable. Before that in the headlines, what we learned about AI and global politics at the g seven. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. Alright, friends. Quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Section, Assembly, and OutSystems. To To get an ad free version of the show, go to patreon.com/aidailybrief, or you can subscribe on Apple Podcasts. To learn more about sponsoring the show, send us a note at sponsors@aidailybrief.ai. You should also check out the new aidailybrief.ai anyways. One of the big things that I have heard from folks is that they want easier ways to share specific parts of these episodes with folks inside their organizations, so that's what we've tried to build with a new website. It divides every episode up into dozens of short easily shareable cards. Lastly, today, there's a link down in the show notes to check out a preview of something that is coming soon, training.bsuper.ai. If you've been following along with the AI DB learning program journey, keep an eye there for some more announcements to come soon. With that, let's talk g seven. Now spoiler alert, we do not have any particularly big updates when it comes to when we're getting Fable five back and the resolution between Anthropic and the US government. However, what we did have was a number of the key players all in the same room as a slew of AI leaders joined the usual heads of state at this year's g seven meeting in France. Sam Altman, Demas Hassabis, Meta's Alexander Wang, and, yes, Dario Almodey were all present as part of The US contingent. France brought along Mistral CEO Arthur Mensch, while Cohere CEO Aiden Gomez attended as part of the Canadian delegation. Another half dozen executives from regional AI champions also attended. Now it is not unusual for executives to attend this sort of diplomatic and trade meeting, but it is certainly the first time that g seven has seen such a heavy representation from the AI industry. And frankly, their attendance makes even more sense in the context of the US government's effective banning of mythos and fable. At a meeting that is all about international cooperation, for the first time, the global community is reckoning with the idea that access to US made frontier models is not a given. Now the pivotal discussion came at a closed door lunch meeting focused on AI and innovation. Flanking Donald Trump on either side were Google DeepMind CEO, Demis Hassabis, and OpenAI, Sam Altman, with Anthropic's Dario Amede being on the exact opposite side of the table next to France's Emmanuel Macron. At the meeting, Amede and Demis Hassabis reportedly led the call for international cooperation on AI risk with The US taking the lead. In his address, Amede said that international cooperation …
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Tools
by Anthropic
“The banning of Anthropic's Claude Fable five model triggers a global scramble for alternatives, as enterprises and governments reassess AI dependency on US frontier models.”
“ZAI's GLM 5.2 ranks first on BridgeBench and Reasoning benchmarks, beating Fable five at one-tenth the cost and 300 tokens per second throughput.”
“Harvey's experiment with Fireworks demonstrates that pairing an open-weight GLM 5.1 worker model with a closed Opus 4.7 advisor — rather than using Opus exclusively — reduced costs significantly while actually improving performance.”
by Anthropic
“Harvey's experiment with Fireworks demonstrates that pairing an open-weight GLM 5.1 worker model with a closed Opus 4.7 advisor — rather than using Opus exclusively — reduced costs significantly while actually improving performance.”
“Harvey's experiment with Fireworks demonstrates that pairing an open-weight GLM 5.1 worker model with a closed Opus 4.7 advisor — rather than using Opus exclusively — reduced costs significantly while actually improving performance.”
“ZAI's GLM 5.2 ranks first on BridgeBench and Reasoning benchmarks, beating Fable five at one-tenth the cost and 300 tokens per second throughput.”
by OpenRouter
“OpenRouter's Fusion API fans prompts out to a panel of models in parallel, each with web search and bash tools, then uses a judge model to synthesize responses.”
“Microsoft is already preparing a locally hosted DeepSeek v4 fine-tune to power Copilot for enterprise customers within weeks.”
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