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DGX Spark

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Headlines · 6

  1. ASUS ProArt P16 review: first NVIDIA RTX Spark laptop arrives

    The ASUS ProArt P16 is among the first laptops to ship with NVIDIA's RTX Spark platform, built around the N1X SoC — a 20-core Arm CPU plus a 6,144-CUDA-core Blackwell GPU, both on TSMC 3nm — supporting up to 128GB of LPDDR5X unified memory, roughly 300 GB/s of bandwidth and 1,000 TOPS of NVFP4 AI compute. Wccftech's early benchmarks show class-leading memory bandwidth but multi-core and single-core 3DMark CPU Profile scores behind x86 rivals such as the Core Ultra X9 388H and Ryzen AI MAX+ 395. NVIDIA claims the laptop can sustain full performance on battery, pricing has not been announced, and further benchmarks are still pending.

    Wccftech · 🔥 9
  2. Sipeed unveils MaixStation, a $3,999 Chinese rival to Nvidia's DGX Spark

    Sipeed announced the MaixStation, a mini PC built on Axera's new AX8860P: 16 Arm Cortex-A55 cores plus an in-house NPU rated at 256 TOPS FP4 without sparsity, with 128GB of LPDDR5X on a 256-bit bus at 273 GB/s, running Debian 13 and Linux 6.18. Sipeed told Tom's Hardware the 128GB model should cost about $3,999, with a Kickstarter campaign at the end of the year, shipping within three months of it closing, and an NPU toolchain due by the end of this month; the company claims vLLM, SGLang and PyTorch support. It says a single node runs Qwen 27B with 25% faster prefill and 30% faster decode than the DGX Spark, but in its email claims only about a 10% lead on both with FP4 on each machine and speculative decoding off, calling wider-margin runs unofficial. For comparison, the 128GB DGX Spark lists at $6,950 and the 128GB AMD Ryzen AI Halo at $3,999.99.

    Tom’s Hardware · 🔥 4
  3. NVIDIA releases Nemotron 3.5 Super VL and two Bolt edge models

    NVIDIA released Nemotron 3.5 Super VL on Oct. 15, an open multimodal model with 120B total and 12B active parameters in a mixture-of-experts design that combines reasoning, instruction following and tool use with text, image, document and video understanding for long-running agents. NVIDIA claims it reaches up to 5x the agentic throughput of other open models in its size class on a single GPU — over 600 output tokens per second at 100,000 input tokens — scores 80.8% on the CharXiv chart-reasoning benchmark (84% with Python code interpretation), and supports NVFP4 quantization and multi-token prediction; BF16 and NVFP4 weights are on Hugging Face with same-day vLLM and Baseten support. Alongside it, NVIDIA launched two Nemotron 3.5 Bolt edge models: Bolt 74B-A9B 24GB, which uses native 2-bit quantization to fit in 24GB of memory and is available now, and Bolt E4B 4GB, due Oct. 23.

    vLLM Blog · 🔥 63
  4. Four Tesla V100 GPUs beat two DGX Spark units in inference test

    The YouTube channel Jun Yamog posted an Oct 12 test running four 2017-era Nvidia Tesla V100 data-center GPUs on an NVLink carrier board with a 4-bit quantized Qwen3.8-Flash-Next model. The cluster was reported 40% faster than two DGX Spark units and 230% faster than an M5 Ultra Mac Studio on long-prompt processing, and 40% and 163% faster respectively on short prompts. Short-prompt token generation reached 100.6 tok/s, about 121% faster than the two DGX Sparks, while the M5 Ultra measured 44.5 tok/s. The tester said the large gap versus Apple Silicon may partly reflect weaker software optimization.

    IT之家 AI · 🔥 0
  5. Microsoft's Surface Laptop Ultra with Nvidia RTX Spark starts at $2,599; Dev Box $5,999

    Microsoft unveiled its new Surface Laptop Ultra, presented by CEO Satya Nadella and Nvidia CEO Jensen Huang, built on Nvidia's RTX Spark platform (a chip co-developed with MediaTek) with up to 128GB of unified memory. According to cnBeta, the laptop starts at $2,599 in the US with shipments scheduled for the following Friday, offering a 15-inch mini-LED touchscreen, up to 1 petaflop of AI performance, and support for running local models with up to 120 billion parameters. Microsoft also opened preorders for the developer-focused Surface RTX Spark Dev Box at $5,999 with 128GB of unified memory, shipping in November with a Project Zenith Windows 11 Pro setup and preinstalled tools including Visual Studio Code, Git, GitHub CLI and GitHub Copilot.

    The Next Web · 🔥 0
  6. Qwen3.8 27B sums big numbers in words, hitting 167/169 with reasoning on

    Simon Willison re-ran an experiment Colin Frasier first tried two years ago with GPT-4o: have a model compute large sums but return the answer in words. He ran it on local hardware (a DGX Spark), using a Codex Remote session (GPT-6 Astra) to write and execute the test with Qwen3.8-27B-Q4_K_M.gguf. With reasoning disabled he sampled 30 attempts per cell; with reasoning enabled each run took so long that he used one sample per pair, and the model got 167 of 169 attempts right.

    Simon Willison's Weblog · 🔥 0

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