NVIDIA AI Infrastructure
@NVIDIAAIInfra
AI factories for the era of AI reasoning.
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🎉 Excited for our partner @SpaceX to try out the NVIDIA Vera CPU.
This is just the beginning for Vera, our CPU purpose-built for agentic AI.
Thank you to @elonmusk and the SpaceX team 🚀
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What does it take to serve agentic workloads on trillion-parameter models at 400 tokens per second per user — without trading throughput for latency?
The NVIDIA Vera Rubin platform pairs Vera Rubin NVL72 with NVIDIA Groq 3 LPX to deliver low latency on trillion-parameter MoE models with 400K-token context with a 35x higher throughput per megawatt.
Learn how the deterministic LPU chip-to-chip (C2C) fabric and extreme co-design address agentic AI's scale-up challenges. ➡️
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💡 Why did @togethercompute choose NVIDIA Blackwell to serve DeepSeek-V4?
Because NVIDIA Blackwell is built for the bottlenecks that matter most in long-context inference:
→ KV-cache pressure during decode
→ MoE weight bandwidth during prefill
A single NVIDIA HGX B200 system can keep DeepSeek-V4’s compressed CSA/HCA/SWA cache layouts resident across many concurrent long-context requests, while native MXFP4 support enables efficient end-to-end quantized inference for V4’s MoE weights.
The result? Higher throughput, lower overhead, and optimized serving efficiency at scale.
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💡 One AI factory. 1,016 NVIDIA Blackwell Ultra GPUs. Over 9,000 petaFLOPs of AI performance.
@EliLillyandCo and NVIDIA launch LillyPod, the world's first #NVIDIADGX# SuperPOD with DGX B300 systems to accelerate drug discovery, medical research, operational efficiency, and enhance industry collaboration.
Together, by combining science, data, and compute power, we're breaking new ground for AI in life sciences.
Learn how we're advancing the broader biotech ecosystem. ➡️
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