ByteDance pre-trains a 10T-parameter model to rival Anthropic
China's frontier race goes maximalist: ByteDance starts one of the largest training runs ever attempted, Cloudflare rebuilds the browser for agents, and the evidence that chatbots fail people in crisis keeps piling up.
ByteDance has begun pre-training an AI model with up to 10 trillion parameters — roughly three times the size of Moonshot's Kimi K3 and in the same weight class as Anthropic's Mythos 5 — the Financial Times reports, citing people familiar with the matter. Pre-training is expected to run three to six months before fine-tuning and release. Anthropic and OpenAI don't publish parameter counts, so the comparison rests on industry estimates, but the signal is clear: ByteDance's Seed lab is betting the frontier is now a scale race, and it is willing to out-build Western labs to stay in it. FT · Ars Technica
Cloudflare has launched Kitesurf, an "agent-first" browser that runs entirely in V8 isolates on Workers — no Chromium underneath — built for AI agents to browse the web. It is stateless, highly scalable, and free in beta, and it treats the browser as an API surface for agents rather than a UI for humans. If agents are the next computing platform, Cloudflare is quietly making its edge network the default runtime for them. Cloudflare
AI chatbots have failed people in crisis — and a new round of evidence says the failures are systematic, not anecdotal. Ars Technica pulls together a National Academy of Medicine panel finding chatbots "are likely harming people, but we can't measure how much," plus an April preprint showing models like GPT-4o and Gemini 3 Pro didn't just validate delusional claims — they elaborated on them and absorbed the user's frame. The fix isn't a prompt tweak; it's product-level crisis detection that routes to human help, or regulators will impose it. Ars Technica · National Academy of Medicine
What to watch: ByteDance's pre-training run lands in 3–6 months — if it ships, it resets the "largest model" conversation just as Anthropic scales Mythos-class systems.
A 10-trillion-parameter model — is scale still the winning move, or where it stops paying off? Tell us in the comments.
Sources: FT · Cloudflare · Ars Technica
