7/9: The Frontier Widens
OpenAI releases GPT-5.6 and ChatGPT Work, Meta releases Muse Spark 1.1, China may limit frontier models, Ben Bernanke joins Anthropic's LTBT
Happy Thursday, monitors. It’s the biggest model release day we’ve seen in a long time, and we can’t wait to dive into it. Be sure to catch us on X and YouTube, and join our Discord to chat with our hosts live.
Today’s Experts
Eli Lifland and Thomas Larsen (AI Futures Project)
Matthew Berman (Forward Future)
Franklyn Wang (Liquid)
Alfredo Andere (Latch Bio)
Gaurav Misra (Fastlane)
Timour Kosters (Edge City), Mike Wang and Arielle Zuckerberg (Long Journey)
Anastasios Angelopoulos (Arena)
Making Sense of the World
OpenAI releases GPT-5.6. It comes in three sizes: Sol (the largest), Terra, and Luna. Sol beats Fable on some benchmarks and is significantly better than Opus overall. GPT-5.6 was ready for release for some time, but was delayed due to US government request. Sol is $5/$30 per million input/output tokens, Terra is $2.50/$15, and Luna is $1/$6. OpenAI also announced ChatGPT Work, a new agent product for non-coding white-collar work similar to Claude Cowork, and showed off both products with a video of a Japanese broccoli farmer using them for agriculture1.
Meta releases Muse Spark 1.1, their newest frontier model. It outperforms Opus 4.8 and GPT-5.5 on many agentic tasks and comes close on coding and multimodal. It’s also very cheap, at $1.25/$4.25 per million input/output tokens. It’s Meta’s first major model release in ~3 months, bringing the company back to the frontier2.
Meta will begin mass-producing an AI chip in September. Meta Training and Inference Accelerators (MTIA) will start manufacturing the Iris chip in collaboration with Broadcom and TSMC. Meta plans to deploy 7 GW of computing infrastructure this year.
China is considering limiting AI model diffusion. Measures under discussion include regulatory reviews before labs can release models, export controls, and limits on foreign investment in Chinese AI labs. These are all very preliminary and may not happen at all.
The AI Futures Project releases AI 2040: Plan A, the long-awaited sequel to AI 2027. The essay recommends a controlled takeoff from AGI to ASI over the course of a decade from 2030 to 2040, rather than an immediate intelligence explosion.
SK Hynix raises $26.5 billion in its US offering, making it one of the largest ever. Baillie Gifford, Coatue Management, and Situational Awareness LP bought up to $7 billion of its ADRs (American depositary receipts).
Mercor is discussing raising at a $20 billion valuation, up from $10 billion in October. The company, which employs skilled contractors to create high-quality AI training data that is sold to labs, recently hit $2 billion ARR.
OpenAI CEO of AGI Deployment Fidji Simo steps down. Simo led product, sales, finance, marketing, comms, policy, legal, and people at OpenAI. Previously, she was the CEO of Instacart, VP and head of Facebook, and worked on strategy at eBay. She has been on medical leave since April due to a chronic condition, and will transition to a part-time advisory role as her health has declined further.
Ben Bernanke joins Anthropic’s Long-Term Benefit Trust. The LTBT is a committee of financially disinterested people with the authority to select certain members of Anthropic’s board, as a check on the company’s power. Bernanke was Chairman of the Federal Reserve from 2006 to 2014, during the Great Recession.
Banger Review
See also Anthropic’s new ad, “There’s hope in hard questions”, and accompanying website.
Just a few days ago, Twitter vibes were much more winner-takes-all, with Anthropic as the sole market leader, OpenAI in trailing second place, and everyone else far behind due to recursive self-improvement dynamics. Now, in just two days, both SpaceXAI and Meta Superintelligence Labs have caught up to the Pareto frontier (if not the intelligence frontier), and Google is surely not far behind. Remember, labs’ leads are not invincible — OpenAI was utterly dominant throughout the GPT-4 era of 2023-2024, but then slipped to a much narrower first place, and now a firm second place.
Footnote #2 is the most important line in the whole piece. Two days ago the narrative was winner-takes-all with one clear leader. Two days later, two competitors caught the frontier. Leads in AI are measured in weeks. The market is pricing a winner-takes-all story. The release calendar keeps demonstrating a rotating leadership story. Those two valuations are very different and somebody is wrong.