Breaking VRAM Limits? The Impact of Next-Generation Technology "vLLM"
Published:Dec 28, 2025 10:50
•1 min read
•Zenn AI
Analysis
The article discusses vLLM, a new technology aiming to overcome the VRAM limitations that hinder the performance of Large Language Models (LLMs). It highlights the problem of insufficient VRAM, especially when dealing with long context windows, and the high cost of powerful GPUs like the H100. The core of vLLM is "PagedAttention," a software architecture optimization technique designed to dramatically improve throughput. This suggests a shift towards software-based solutions to address hardware constraints in AI, potentially making LLMs more accessible and efficient.
Key Takeaways
- •vLLM is a new technology that aims to improve LLM performance by optimizing VRAM usage.
- •The core technology behind vLLM is "PagedAttention," a software architecture optimization.
- •This approach could make LLMs more accessible and efficient by mitigating hardware limitations.
Reference
“The article doesn't contain a direct quote, but the core idea is that "vLLM" and "PagedAttention" are optimizing the software architecture to overcome the physical limitations of VRAM.”