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NVIDIA unveils RTX PRO 5500 Blackwell workstation GPU with 84GB

NVIDIA launches an 84GB Blackwell workstation GPU, QLNI ships a 19.8 MB CPU model, and Intern releases a 397B multimodal scientific model.

๐Ÿš€ RELEASES & LAUNCHES

  • NVIDIA unveils RTX PRO 5500 Blackwell workstation GPU with 84GB
    NVIDIA unveiled the RTX PRO 5500 Blackwell workstation GPU with 84GB of GDDR7 memory.
    • Designed for enterprise teams running agentic AI, physical simulation, graphics, rendering and compute workloads.
    • The rack-mountable GPU includes 84GB of GDDR7 memory, fifth-generation Tensor Cores, fourth-generation RT Cores and support for air- or liquid-cooled configurations.
    • It supports up to two isolated Multi-Instance GPU partitions, enabling shared workstation acceleration with guaranteed quality of service.
    • NVIDIA lists the RTX PRO 5500 as coming soon, with availability notifications offered through its product page.
    Sources ๐Ÿ“Ž Coverage: nvidia.com ยท ๐Ÿ‘ via r/LocalLLaMA

๐Ÿ”ฌ RESEARCH

  • QLNI publishes 19.8 MB SHADOW 50M model with exact circuits and disk memory
    QLNI released SHADOW 50M, a 44M-parameter model for offline CPU inference with disk-based memory.

    • The model targets developers building offline, CPU-based, browser, and edge applications.
    • SHADOW 50M has 44.1M ternary parameters, a 19.8 MB deployment file, and an 8,192-token context.
    • It runs at about 2,000 tokens per second in 40 MB of RAM and supports a 100M-token on-disk archive with 0.03 ms fetches.
    • Built-in circuits compute arithmetic, dates, units, counting, and sorting without tools, networks, or interpreters.
    Sources ๐Ÿ“„ Source: huggingface.co ยท ๐Ÿ“Ž Coverage: github.com ยท ๐Ÿ‘ via r/MachineLearning
  • ๐Ÿ“„ Source for Intern Large Models releases 397B multimodal scientific model โ€” x.com

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