Nvidia: GB300 Delivers 25x Higher Energy Efficiency Than Hopper for DeepSeek V4 Pro
nvidia · x · 2026-07-15
Nvidia officially stated that when running the DeepSeek V4 Pro model, the NVIDIA GB300 NVL72 system can achieve up to 25 times the performance per watt (energy efficiency) of the Hopper architecture. The company emphasized that in today's power-constrained AI factory environments, performance per watt is the most fundamental core metric.
Related event: NVIDIA Emphasizes Performance-per-Watt for AI Infrastructure(4 posts)→
More from Infra
- 12 KV Cache Reduction Techniques Every AI Engineer Should Understand, Explained — blaizedsouza · 2026-09-11
- The shadow GPU capacity market is formalizing, with Meta selling excess compute to outside buyers — DavidLinthicum · 2026-09-11
- Engram's random reads don't suit SSDs; CPU-memory over NVLink could serve all 72 GPUs — bookwormengr · 2026-09-11
- 80% of the DIY LLM inference hype posters have already quit — it's brutally hard systems work — abhijithneil · 2026-09-11
- Hugging Face's Ultra Scale Playbook: a free book on training LLMs on GPU clusters — mdancho84 · 2026-09-11
- Is inference latency becoming the biggest bottleneck for production AI agents? — Euphoric_Sea632 · 2026-09-11