NVIDIA Jetson Thor

Headlines · 2

1. 5d
   Embedl reports Qwen3.8-27B deployment at 40 tok/s on Jetson Thor

   Embedl reported a Qwen3.8-27B deployment on NVIDIA Jetson Thor using INT4 weights, an MTP head for speculative decoding, FlashHead, and TensorRT Edge-LLM 0.10.1. Under its stated batch-one test setup, the company reported 39.6 tokens per second for decoding, 23.6 end to end, 926 tokens per second for prompt processing, and peak memory of 24.8 GiB. The r/LocalLLaMA post also reports near-FP16 benchmark results, but the deployment and performance figures are vendor claims without independent confirmation.

   r/LocalLLaMA · 🔥 0
2. Oct 23
   ASUS sponsors edge AI hackathon with Ascent GX10 and PE3000N

   TechNews reports that the 2026 Agentic AI on the Edge Hackathon, sponsored by ASUS, took place October 21–22 at the Bottle Cap Factory in Nangang, Taipei; the same report also describes three days of development, an inconsistency it does not resolve. The report says 15 teams proposed solutions for smart manufacturing, automated services and smart retail. ASUS supplied its Ascent GX10 desktop AI supercomputer, described as based on the NVIDIA DGX Spark architecture with a GB10 Grace Blackwell Superchip, and its PE3000N rugged edge system built on an NVIDIA Jetson Thor module. According to ASUS, the GX10 supports NVIDIA's NemoClaw open agent blueprint for sandboxed, access-controlled on-device inference, while the PE3000N supports hardware sensor fusion and NVIDIA Isaac and Metropolis software stacks.

   科技新报 · 🔥 0

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