SemiAnalysis on $META “overcapacity” and market reactions with $NBIS and others: “We believe Meta’s datacenter and compute will accelerate”. “Capex in 2027 will be shockingly high”. Recent global crash, especially in the photonics sector was stupid… Off misleading narratives of Meta dropping out of AI race to sell excess compute… When in fact things are likely to accelerate from Meta catching up to GPT5.5. I’m personally expecting a sharp V recovery, especially with the names that crashed 50%+ from this narrative.

The future of AI isn't just about the model - it’s about the memory. 🧠✨ We are excited to announce that new model from @Openai GPT-5.5 is now integrated into the ZetaChain ecosystem! Experience the convenience of a persistent, user-owned memory layer that integrates fluidly with every AI model. ✅ Multi-model support ✅ Private & Decentralized ✅ Consistent memory across models Stop switching and losing context. Start building with a universal memory layer on ZetaChain. #ZetaChain# #GPT5# #AI# #DecentralizedAI# #Web3Innovation# #OpenAI#

⚡ Stop treating intelligence and efficiency as separate. GPT-5.6 maximizes intelligence per token to deliver equal-or-better performance more cheaply and quickly. Title: How GPT-5.6 fuses frontier intelligence with frontier efficiency URL: ⚡ Overview GPT-5.6 is trained to optimize both task success and efficiency, taking a more direct path through tasks. OpenAI calls it their greatest intelligence-per-token efficiency yet. 🧩 Problem Solved Frontier models are smart, but reasoning tokens, latency, and cost are the wall in production. GPT-5.6 makes efficiency a first-class goal, pushing the performance-vs-cost tradeoff outward. 🛠 Methodology & Lineup ・Sol: flagship for frontier reasoning and long-horizon agentic work ・Terra: everyday balanced model, GPT-5.5-competitive at about half the cost ・Luna: fastest and cheapest (~80% less than Sol) On serving: improved speculative decoding gives 15%+ better token generation, and GPU kernel improvements cut serving cost 20%. 📊 Results On the Artificial Analysis Coding Agent Index, Sol (max reasoning) sets a new SOTA of 80, beating Fable 5 by +2.8 while using under half the output tokens, half the time, and ~1/3 less cost. On ExploitBench it matches Mythos Preview using ~1/3 of the output tokens. #GPT56# #OpenAI#

GPT Astra is going to be the best model in the world. GPT 5.6 Sol never fixed hallucinations. Opus 5 flopped. Too slow, too lazy, no traction. Fable 5 is still great but it is four months old now (Project Glasswing), and the hype is gone. Meanwhile the US keeps slowing releases down. Fable 5 got export controlled in June. Now there is a process frontier labs must undergo before they release new models publicly. GPT Astra is a new pretrain which is what it takes to get new leaps in capability. This is the one.

GPT 5.6 Terra and Luna are now live in Perplexity Computer. Terra is the new default model for all Computer subagents, while Luna will serve as the primary model for scheduled automations. Terra is also available as an orchestrator model in Computer.

GPT-5.6 Terra and Luna just got price cuts from @OpenAI. OpenRouter is cheaper still. Our 50% exclusive discount applies on top, bringing Luna to $0.1/M in $0.6/M out and Terra to $1/M in and $6/M out. Scale your workloads with luna:

GPT-5.6 Sol, running in Codex, helped make GPT-5.6 cheaper to run. It rewrote production GPU kernels and helped improve the smaller model used to speed up generation. Kernel improvements helped cut end-to-end serving costs by 20%.

GPT-5.6 Sol sets a new state of the art in cybersecurity on “The Last Ones” cyber range. We’re already seeing that capability translate into defensive outcomes: helping teams find, validate, and fix vulnerabilities in real-world code. Put it to work with Codex Security: