🚀 RELEASES & LAUNCHES
- OpenMed 3.0 launches as a local, Apache-2.0 clinical AI toolkit
OpenMed released version 3.0, an offline Apache-2.0 clinical AI toolkit.- For healthcare developers and organizations handling patient data.
- OpenMed 3.0 runs locally without API keys or cloud calls and supports 2,200+ open models.
- Models can run through Transformers, ONNX, GGUF with llama.cpp, WebGPU/WASM in browsers, or on phones.
- The release gives builders offline deployment options for clinical AI workflows and keeps patient data on-device.
📊 BENCHMARKS & EVALS
- vLLM-Ascend Updates Bring GLM-5.3-Flash to Dual Ascend 310P Cards
A community setup runs GLM-5.3-Flash on dual Ascend 310P cards.- Targets local inference developers using dual 96GB Ascend 310P cards.
- The setup runs GLM-5.3-Flash, a 320B-parameter MoE model with about 18B active parameters per token.
- The checkpoint uses 45 layers, 288 experts, top-8 routing, and W2/W3/W4 quantization.
- Hot-swapping modules, CANNs, and server changes while keeping model weights resident speeds up experimentation.
Sources 📎 Coverage: reddit.com · 👁 via r/LocalLLaMA
💰 BUSINESS & FUNDING
- Nvidia explores acquiring or investing more in Reflection AI
Nvidia is in preliminary talks to acquire or invest more in Reflection AI.- The discussions involve Nvidia and Reflection AI, a U.S. startup developing open-weight models for enterprise and public-sector AI users.
- Nvidia has reportedly invested $800 million in Reflection AI and is considering a full acquisition, additional equity, or an acqui-hire arrangement.
- Reflection AI’s Beam model has 501 billion total parameters and activates 23 billion per token through a sparse Mixture-of-Experts architecture.
- A deal would give Nvidia greater control over frontier open-weight model development alongside its AI chips and computing infrastructure.
Sources 📎 Coverage: finance.biggo.com · 👁 via r/LocalLLaMA