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Open-Weight Models

331 summarised stories about Open-Weight Models, each linking back to the original source. Browse all topics →

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Wednesday, 7 October 2026

China's AI startups can match the U.S.'s models. They can't yet match the U.S.'s money

Fortune 24 ● 6 sources

China’s AI startups are nearing U.S. model performance, with analysts estimating the best Chinese models are about four months behind OpenAI and Anthropic. Chinese venture funding for AI start-ups from 2023 to 2026 totaled under about $38 billion versus the U.S.’s $380 billion-plus. The next wave of Chinese AI development will therefore depend more on non-traditional financing—such as Hong Kong IPOs and private credit—rather than just U.S.-scale venture capital.

Windows Gets Open-Weight A.I. Like China’s DeepSeek and Nvidia’s Nemotron

Trending Topics 2 weeks ago 2 ● 12 sources

Microsoft announced Windows as a more secure “hybrid intelligence” platform where AI agents can run locally or in the cloud inside OS sandboxes with company-controlled access rules. Surface Laptop Ultra with Nvidia’s RTX Spark chip starts preorders at $2,599 and is slated to ship from next Friday. Microsoft will generally release Windows 11 Microsoft Execution Containers (MXC), add Copilot local-file and search command actions to Copilot+ PCs, and expand the set of on-device model providers beyond OpenAI.

Liquid AI Releases Open-Weight d1-3B and d1-omni-600M: Multimodal Decision Models With Zero Output Tokens

MarkTechPost 2 weeks ago 39 ● 8 sources

Liquid AI released Open d1, two open-weight multimodal decision models (d1-3B and d1-omni-600M) that return calibrated typed answers with zero output tokens. d1-3B scored 48.57 on Decision Index v0.2.1 and takes 8 ms for one question on an RTX 4090. The models shift deployments from generating token-by-token text to making real-time probabilistic decisions across fixed options, including text+image and text+audio inputs.

Multimodal open d1 decision models for the edge

Hugging Face 2 weeks ago 45 ● 8 sources

Liquid AI released two open-weight d1 decision models for edge use: d1-3B and experimental d1-omni-600M. d1-3B scored 82.9 mean on seven public datasets and answered a single question in 16 ms on an NVIDIA Jetson AGX Thor. The models provide fast single-forward-pass multimodal decision outputs (text+image for d1-3B, and text+image or text+audio for d1-omni-600M) and are now available on Hugging Face with usage code.

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