Open Source

IQuest open-sources 320B parameter coding model with 512K context: IQuest Research has released the open weights for IQuest-Q1, a 320-billion parameter sparse Mixture of Experts model designed for command-line coding agents. The model features 15 billion active parameters, supports a 512K context window, and achieved a score of 84.5 on the CyberGym benchmark.

AI Models • Pandaily

DeepSeek open-sources Ascend AI libraries as Huawei details SuperPoD Flex: DeepSeek has open-sourced Ascend-compatible versions of its AI libraries, including TileLang, DeepGEMM, DeepEP, TileKernels, FlashMLA, and DeepSelect. Concurrently, Huawei detailed a jointly defined 128-card SuperPoD Flex hardware design.

Infrastructure • Pandaily

Hugging Face • OpenAI

OpenAI offered $100 million to Hugging Face before Nvidia acquisition: Before Nvidia agreed to acquire open-source platform Hugging Face for approximately $13 billion, OpenAI offered to invest around $100 million in the startup. The investment talks between OpenAI and Hugging Face ultimately fell apart. AMD and Salesforce also reportedly held talks with Hugging Face.

Huawei open-sources training and RL code for openPangu-2.0: Huawei's Ascend Tribe has open-sourced the pretraining, supervised fine-tuning, and reinforcement-learning code for its openPangu-2.0 model family. The release includes openPangu-2.0-Training and openPangu-2.0-RL. The code is optimized for Huawei's Ascend-based training ecosystem.

AI Infrastructure • TechNode

NaiveAI releases open-weights 309B parameter MoE model: NaiveAI has released Naive-N0.5-Flash under an MIT license. The 309-billion-parameter Mixture-of-Experts model features 15.5 billion active parameters and a native 1-million-token context window. Built on MiMo-V2.5 without full-attention layers, it is designed for coding and AI research.

AI Models • Pandaily