#china
Wiki 25
- 6 months to live for open models Lambert predicts a US ban or delay on frontier open weights by early 2027, calls Anthropic's distillation campaign regulatory capture, and proposes off-ramps
- Are Open Models Catching Up? SemiAnalysis reruns era-specific benchmarks on open and closed LLMs and finds catch-up time roughly halving each era, from 19.7 to 4.8 months
- Banning Open Source AI Would Be A Mistake Lambert and Kevin Xu's 2026 op-ed defending open source AI on education, innovation and competition as Washington moves to regulate models
- China's Structural Advantage in Open Source AI Kevin Xu, after Ion Stoica, on why Chinese labs default to open weights - talent, data, academia-industry ties, and shared artifacts
- Chinese Open Source: A Definitive History Kevin Xu traces Chinese open source from Linux in 1994 through Alibaba, Kaiyuanshe, Huawei and the state to the DeepSeek-era AI labs
- DeepSeek Chinese AI lab whose V3/R1/V4 model line drove the open-weights reasoning-model cost-collapse story of 2024-2026
- DeepSeek V4 Flash 0731 scores 50 on the Artificial Analysis Intelligence Index, 10 points above previous DeepSeek V4 Flash Artificial Analysis puts DeepSeek V4 Flash 0731 at 50, one point under GPT-5.6 Luna for ~60% less per task and on the cost Pareto frontier
- Detecting and countering misuse of AI: September 2026 Anthropic's threat report on Claude misuse from Dec 2025 to Aug 2026, led by seven Chinese labs said to distill Claude and pass it off as their own models
- From Open Source Software to Open Source Strategy Bill Gurley on open source as a corporate weapon, from Android and Kubernetes to autonomous vehicles and the fight over open-weight AI
- GLM-5.2 is the step change for open agents Nathan Lambert on GLM-5.2 as the first open-weight model that works as a general coding agent, released while Claude Fable 5 was restricted
- GLM-5.3: How Chinese labs keep stride with the frontier Lambert on GLM-5.3 and why Chinese labs match US models without relying mainly on distillation, plus Z.ai's staged release for cyber capabilities
- How far behind are open models? Håvard Tveit Ihle measures open-model lag on 17 benchmarks, finding 8-10 months on private ones, 4-6 on public, and a gap growing since R1
- How much does distillation really matter for Chinese LLMs? Lambert reads Anthropic's February 2026 disclosure against DeepSeek, Moonshot and MiniMax and argues distillation helps but is not decisive
- Kimi K3: The open-weights escalation Nathan Lambert on Kimi K3 as the first true frontier open-weight model, what it says about Chinese labs, and why banning open weights backfires
- LLM Distillation Training one LLM on another's outputs, from SFT on generated text to on-policy KD, and the 2025-2026 fight over Chinese labs distilling US models
- Notes from inside China's AI labs Nathan Lambert's May 2026 trip report from Chinese AI labs - student-heavy teams, less ego, Claude everywhere, in-house data, and too few Nvidia chips
- Open models in perpetual catch-up Nathan Lambert on why the roughly six-month gap between open and closed models holds steady, plus trends in adoption, specialization and China
- Open-closed model gap How far the best open-weight LLMs trail the best closed ones - how it is measured, estimates from 4 to 10 months, and whether it closes
- Open-Source AI & Open Models Reading List Nathan Lambert's annotated list of the best writing on open models — why they exist, why China leads, the gap, cyber risk and distillation
- The ATOM Project: American Truly Open Models Nathan Lambert's 2025 memo arguing the US lost open-model leadership to China and needs several 10,000-GPU labs building fully open models
- The ATOM Report: Measuring the Open Language Model Ecosystem Lambert and Brand's 2026 adoption study of ~1.5K open models - China passed the US in downloads in mid-2025, Qwen dominates, plus a size-normalized metric
- The distillation panic Lambert argues "distillation attacks" wrongly brands a standard training technique and warns US policy could end up banning Chinese open weights
- The Z.ai Playbook ChinaTalk interviews Z.ai's Zixuan Li on GLM - why Zhipu open-sources, the coding plan, role-play and translation, release within hours
- US Scrutiny of Chinese Model Use House probes of Airbnb, Cursor and DoorDash over Chinese AI models, set against Western companies moving to Chinese open weights to cut costs
- Z.ai (Zhipu AI) Chinese lab behind the open-weight GLM models, from a 2021 Tsinghua paper to GLM-5.3, and how its release practice changed along the way
talks 1
- Nathan Lambert on China's AI Ecosystem and the Open Model Gap Lambert's 2025 recap of open models - Qwen overtaking Llama, a crowded Chinese field, and why the US needs funded, fully open models