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Friday

  1. The Verge AI

    One week with RTX Spark laptops: How do gaming, local AI, and battery life perform?

    Three authors from The Verge spent a week testing five laptops powered by Nvidia's RTX Spark N1X chip, including the 128GB Surface Laptop Ultra, Asus ProArt P16, Lenovo Yoga 9n, and HP OmniBook Ultra, priced from $3,199.99 to $6,999.99. For gaming, medium settings plus DLSS Performance mode held a steady 60fps in most games, but CPU-bound scenarios such as Helldivers 2 struggled to hit that mark; the authors place its graphics performance roughly between the RTX 5070 and RTX 5060 Laptop GPU. The local AI experience still feels like a developer testing phase: generating a news briefing with Qwen3.8-27B took 10 minutes and consumed 10% of the battery, while battery life for web-based office work came in at around 5 hours.

    Three authors from The Verge spent a week testing five laptops powered by Nvidia's RTX Spark N1X chip, including the 128GB Surface Laptop Ultra, Asus ProArt P16, Lenovo Yoga 9n, and HP OmniBook Ultra, priced from $3,199.99 to $6,999.99. For gaming, medium settings plus DLSS Performance mode held a steady 60fps in most games, but CPU-bound scenarios such as Helldivers 2 struggled to hit that mark; the authors place its graphics performance roughly between the RTX 5070 and RTX 5060 Laptop GPU. The

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    #tech-media#Evaluations / benchmarks#English text is being prepared.#English text is being prepared.
  4. The New Stack

    Running local AI models on the Microsoft Surface Laptop Ultra: hands-on findings

    The New Stack tested running local AI models on the Microsoft Surface Laptop Ultra (Nvidia N1X platform, Blackwell RTX GPU, 64GB of memory, $4,300 configuration): Nemotron 3.5 Bolt reached 56-60 tokens/s, while 8-bit Qwen 3.8 27B managed only 8-9 tokens/s, recovering to 25-28 tokens/s after dropping to 4-bit. On battery, AI workload performance dropped by about 20%-25%, inconsistent with Microsoft's claim of retaining 99.6%.

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    #hot-signal#Evaluations / benchmarks#English text is being prepared.#English text is being prepared.
  8. Artificial Analysis full articleSelected

    Reflection Releases Its First Model Beam, Scoring 30 on the Artificial Analysis Intelligence Index

    Reflection has released its first model, Beam, an open-weight model with 501B total parameters and 23B activated parameters. It scores 30 on the Artificial Analysis Intelligence Index, ranking second among US open-weight models, behind only Meta's Muse Spark Open (39) and ahead of NVIDIA's Nemotron 3.5 Super VL (26). Beam consumes about 26k output tokens per Intelligence Index task, of which about 19k are used for reasoning and 7k for answering; it scores 48.5% on AutomationBench-AA, but only 3.0% on Terminal-Bench 4.0. On AA-Omniscience, it answers 33% of questions correctly, with a hallucination rate of 47% and a net index score of 1.5.

    activated parameters. It scores 30 on the Artificial Analysis Intelligence Index, ranking second among US open-weight models, behind only Meta's Muse Spark Open (39) and ahead of NVIDIA's Nemotron 3.5 Super VL (26). Beam consumes about 26k output tokens per Intelligence Index task, of which about 19k are used for reasoning and 7k for answering; it scores 48.5% on AutomationBench-AA, but only 3.0% on Terminal-Bench 4.0. On AA-Omniscience, it answers 33% of questions correctly, with a hallucinati

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    #company#Model releases#Open-source ecosystem#Evaluations / benchmarks

Thursday