// AI news · 2026-11-06 · NVIDIA Newsroom
NVIDIA's Full-Stack Codesign Boosts AI Memory Efficiency
NVIDIA employs full-stack codesign to optimize memory efficiency across AI systems.
Published 2026-11-06 00:00 (Beijing time)Source NVIDIA NewsroomAuto-summarised, fact-checked against source
01Summary
By integrating GPU, CPU, storage, and software, it reduces model weight footprint using NVFP4 precision and offloads inactive context to lower-cost tiers like CMX. This approach enables higher throughput per dollar in agent-based inference while maintaining performance under growing HBM pressure.
Summarised from the original article by an open-source model, then checked automatically: every number and English name must appear in the source. The original article is authoritative.
02Key points
- Full-stack codesign integrates hardware and software to optimize memory use
- NVFP4 reduces model weight size and distributes across 72 GPUs
- Inactive KV cache is moved to CMX storage for cost-effective retention
- HBM per GPU increases by ~3%, agent throughput per dollar rises up to 30x
03Source
More Performance From Every Byte: How Full-Stack Codesign Solves AI’s Memory Challenge
NVIDIA Newsroom · published 2026-11-06 00:00 Beijing time
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