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NVIDIA AI
NVIDIA
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@NVIDIAAI

NVIDIA AI

NVIDIA
@NVIDIAAI
Teaching your AI new tricks.
Santa Clara, CA
developer.nvidia.com
Joined June 2016
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  • Pinned
    @NVIDIAAI
    NVIDIA AI
    NVIDIA
    @NVIDIAAI
    Aug 11
    Introducing NVIDIA Nemotron 3.5 Lightning⚡ An open 30B MoE model with 3B active parameters, built for always-on agents to complete high-volume, specialized tasks faster. It delivers up to 4x the output speed of similar-sized models.
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  • @NVIDIAAI
    NVIDIA AI
    NVIDIA
    @NVIDIAAI
    Aug 28
    Already running an inference engine? So where does NVIDIA Dynamo fit in? In five minutes, we break down how Dynamo sits around engines like @sgl_project, @vllm_project and TensorRT-LLM to scale inference across GPUs and nodes. Full video in the comments 🔽
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  • @NVIDIAAI
    NVIDIA AI
    NVIDIA
    @NVIDIAAI
    Aug 28
    10 million downloads for NVIDIA Warp 🎉 Warp started with a simple idea: you shouldn’t have to leave Python to get real GPU performance for physics and simulation. Since then, developers have used it to accelerate work across physics simulation, computational engineering,
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  • @NVIDIAAI
    NVIDIA AI
    NVIDIA
    @NVIDIAAI
    Aug 28
    Run Your Polars Code on Multiple GPUs | Live with cuDF Polars
  • @NVIDIAAI
    NVIDIA AI
    NVIDIA
    @NVIDIAAI
    Aug 26
    Congrats to @Alibaba_Qwen on releasing Qwen3.8-Flash-Next, an experimental open-weight model that previews the Qwen4 architecture. We’ve got Day 0 support to fine-tune with NVIDIA NeMo AutoModel and NeMo RL, plus recipes to run it with @sgl_project, @vllm_project and
    @Alibaba_Qwen
    Qwen
    @Alibaba_Qwen
    Aug 26
    ⚡Meet Qwen3.8-Flash, a multimodal MoE and an early preview of the Qwen4 architecture, now open-weight! The production version Qwen3.8-Flash will be available soon via QwenCloud API at just $ 0.16/1M input tokens and $ 0.47/1M output tokens. 125B parameters + 51B N-gram
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REPLAY
@NVIDIAAI
NVIDIA AI
NVIDIA
@NVIDIAAI
Run Your Polars Code on Multiple GPUs | Live with cuDF Polars
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