Simon Willison's Weblog·2 months ago·
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● 33 sources
Moonshot AI released the weights for Kimi K3, a 2.8 trillion parameter model, totaling 1.56TB on Hugging Face. The model's license requires a separate commercial agreement with Moonshot for any Model as a Service business exceeding $20 million in annual revenue. Kimi avoids calling this "open source," instead using "open weight," and OpenRouter is already offering K3 from multiple providers at comparable pricing to Moonshot's official rates.
Anthropic CEO Dario Amodei clarified that the company does not support banning open-weights models and has never advocated for such bans, contrary to recent accusations. Amodei's primary national security concerns are authoritarian governments building more powerful AI models and misuse of AI for cyberattacks or biological attacks, neither of which would be addressed by restricting open-weights models in the US. Instead, Anthropic supports three targeted measures: restricting chip exports to China, cracking down on industrial-scale distillation operations, and requiring mandatory safety testing for all sufficiently capable models regardless of whether they are open or closed.
Moonshot AI released open weights for Kimi K3, a 2.8-trillion-parameter language model, on Hugging Face following overwhelming API demand. Running the model requires approximately 1.4 TB of storage and a distributed GPU environment with at least eight servers equipped with eight NVIDIA H100 or B200 accelerators each. Organizations can now self-host K3 to avoid recurring API costs, though the substantial infrastructure investment makes this option practical primarily for those with strict regulatory requirements or existing GPU capacity.
Moonshot AI, a Chinese startup, released Kimi K3, an AI model that performs comparably to leading US systems at lower cost, and plans to distribute the model's weights for free to developers worldwide. The model reportedly matches or exceeds performance of some top US AI systems while being significantly cheaper to operate. This shift toward open-weight models threatens the market dominance of closed proprietary systems from US companies by giving developers greater control and accessibility to capable alternatives.
Open-weight AI models are becoming a foundational platform for an emerging ecosystem similar to how Kubernetes dominated cloud infrastructure, with Chinese models gaining significant adoption on platforms like Hugging Face. The author argues that imposing restrictions on Chinese open-weight models would isolate US developers from an ecosystem already attracting top global AI talent, whereas the US should instead release frontier-grade models, use procurement to support open standards, and build complementary tools to compete effectively. The outcome determines whether the US remains central to AI innovation or cedes leadership by walling off its developers from the dominant open ecosystem.
Not Boring by Packy McCormick·2 months ago·
11
● 75 sources
Tech leaders including Satya Nadella and Jensen Huang signed a letter supporting open-weight AI models, a move that aligns their commercial interests with consumer benefits by increasing competition and preventing duopolies at the model layer. The signatories span companies that either build open models or benefit from their proliferation, including Nvidia, Microsoft, Meta, and others across the AI ecosystem. This creates a scenario where commoditizing AI as a tool rather than restricting it as a potentially dangerous entity allows more participants to compete and innovate.
Thirty-three companies including Nvidia, Palantir, and Hugging Face formed the Open Secure AI Alliance to develop security tools and techniques for open-weight AI models. The alliance includes major tech firms but notably excludes OpenAI and Anthropic, reflecting the competition between closed and open approaches to AI. The move signals a shift in AI safety focus from auditing closed models to securing the infrastructure layer, including patch cycles and tracking model provenance, since downloaded model weights cannot be easily regulated.
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