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A tweet challenges the claim that Macs are useless for AI without CUDA, presenting benchmarks showing a Mac Mini achieves 56 t/s generation on a 30B model, arguing it's fine for local inference while DGX excels at training and prefill.
Running a 4-bit quantized version of GLM-5.2 (753B MoE) on 4 DGX Spark machines achieves 70.8% on Terminal-Bench 2.1, compared to 81.0% from the full model.
The NAIRR pilot program, powered by NVIDIA AI infrastructure, has supported over 700 research projects, including the development of the Walrus foundation model for fluid simulations and the MIST molecular foundation models for energy storage.
NVIDIA announced RTX Spark PCs and a wave of updates to enable local AI agents across RTX and DGX ecosystems, including the OpenShell runtime coming to Windows, NemoClaw expansion, performance improvements, and integrations with Adobe and H Company.
Noticing price increases for DGX Spark and Strix Halo hardware, suggesting rising demand for local AI computing.
A user reports that their Asus Ascent with Nvidia GB10 (DGX) is slower than their Ryzen AI Max when running LLMs like Gemma4-31B, despite expected 2-4x speedup, and shares their llama-cpp configuration for debugging.
A user reports successfully using tap water to cool a DGX server while running the Qwen3.5-122b model at high GPU utilization, maintaining safe temperatures.