Models & Labs
Apple Intelligence arrives in China via iOS 27.3
The Verge AIhigh confidence
Why it matters
- →Apple Intelligence becomes available to Chinese users for the first time via iOS 27.3.
- →The service relies on Alibaba’s Qwen model instead of OpenAI due to local regulations.
- →Initial features focus on text and image tools, excluding the new generative Siri.
Apple announced that iOS 27.3 will bring Apple Intelligence features to China, starting with a beta release on November 4 and a full launch in December. The update includes notification summaries, real-time translation, rewriting tools, visual intelligence, and object removal from photos. These features are powered by Alibaba’s Qwen model, replacing the OpenAI integration used elsewhere. Notably, the new generative Siri is not included in this initial rollout.
Read originalThe story around this
TopicApple Siri AI
Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
How we got here
- 1Revamped Siri AI Changes iPhone Interaction
The Verge AI · July 13, 2026 · Related
- 2Apple's Siri AI Revamp Debuts in iOS 27 Beta
WIRED AI · July 13, 2026 · Related
- 3Apple Sues OpenAI Over AI Race Expansion
The AI Daily Brief · July 14, 2026 · Background
- 4Apple's Siri AI Opens to Public with iOS 27 Beta
TechCrunch AI · July 14, 2026 · Same story
- 5Apple AI Approved for China with Alibaba, Baidu
TechCrunch AI · July 16, 2026 · Same story
- 6Apple partners with Alibaba for China AI model
The Verge AI · August 14, 2026 · Related
- 7Apple's AI-Focused Mac Minis
The AI Daily Brief · August 29, 2026 · Background
- 8Apple's Siri AI Gets Major Upgrade with iOS 27
WIRED AI · September 10, 2026 · Related
More from The Verge AI
© The Verge AICoding Toolscoding
DIY Muse Gadget proves Meta's hardware is just a dev kit
Meta’s Muse Charm isn’t a finished product; it’s an invitation to hack. A non-coder used Claude Code to transform a $50 Waveshare ESP32-S3 dev board into a fully functional AI companion, adding ElevenLabs voice synthesis, custom Tamagotchi-style minigames, and remote camera controls that Meta’s official firmware lacks. This reveals a critical truth: the value of Meta’s new hardware ecosystem lies not in its out-of-the-box utility, but in its open-source API allowing anyone to rewrite the experience. The gap between Meta’s polished demo and the actual user reality is bridged entirely by third-party AI coding tools.
The Verge AI
© The Verge AIMarket & Regulationbusiness
Altman argues cloud RAM over local inference
Sam Altman is pushing back against the local AI trend, arguing that hoarding DRAM in personal devices is a global waste during a severe supply crunch. He points out that consumer hardware sits idle most of the time, whereas cloud data centers achieve the high utilization rates needed to justify the billions invested by players like OpenAI and Stargate. This isn't just an opinion; it's a defense of the centralized infrastructure model against the growing open-source movement. The real-world impact is visible in the locked-up supply from Samsung and SK Hynix, which drives up costs for everyone else.
The Verge AI
© The Verge AIMarket & Regulationother
Big AI labs back unified opt-out standard
The industry is finally moving past the wild west of web scraping with a unified opt-out signal. OpenAI, Google, Microsoft, and Anthropic have agreed to honor a new IETF-standardized token in robots.txt, allowing publishers to block their content from AI training across all major providers simultaneously. This ends the tedious process of negotiating individual exclusions with each tech giant. While Meta’s commitment remains vague, the consensus among the dominant players establishes a clear precedent for publisher control over data usage.
The Verge AI
More in Models & Labs
Models & Labsmodels
llama.cpp b12029 adds CUDA 13 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally supporting NVIDIA's latest CUDA 13 stack alongside AMD's ROCm 10.0. The inclusion of native builds for Linux arm64 with Snapdragon chips, covering CPU, Adreno GPU, and Hexagon NPU, signals a serious push into mobile edge deployment. While Apple Silicon KleidiAI is disabled in this specific build, the broader hardware coverage means developers no longer need to compile from source for most modern accelerators. It’s less about new features and more about removing friction for anyone running local models on bleeding-edge or diverse hardware.
llama.cpp Releases
© Matt WolfeModels & Labsmodels
Google Releases Gemini 4 Carbon for Cost-Efficient Inference
Google launched Gemini 4 Carbon, a new model variant aimed at providing high performance at a lower cost for inference tasks.
Matt Wolfe
© Lev SelectorModels & Labsmodels
Google Gemini 4 Carbon Leads LM Arena Leaderboard
Google's new model, Gemini 4 Carbon, has taken the top spot on the LMSYS Chatbot Arena leaderboard.
Lev Selector