// AI news · 2026-11-06 · IT之家
NVIDIA Boosts Smart Agent Throughput per Dollar
NVIDIA introduces a holistic design approach to improve smart agent throughput per dollar, achieving up to 30x gains with only a 3% increase in HBM capacity.
Published 2026-11-06 07:30 (Beijing time)Source IT之家Auto-summarised, fact-checked against source
01Summary
The solution uses NVFP4 quantization, context offloading to CPU and storage, and dynamic migration via Dynamo software to reduce memory pressure. Performance is demonstrated under 125 tokens per user per second, showing that AI efficiency is shifting from raw memory size to cost-effective token output.
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
- 30x increase in smart agent throughput per dollar with only 3% HBM capacity growth.
- NVFP4 quantization reduces model and KV cache memory footprint.
- Context offloading to CPU and storage minimizes GPU memory usage.
- RAG indexing stored outside HBM to avoid long-term occupancy.
03Source
英伟达破局 AI 内存瓶颈：HBM 仅增约 3%，每美元智能体吞吐量最高提升 30 倍
IT之家 · published 2026-11-06 07:30 Beijing time
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