
KV Cache Quantization: Fitting Larger Context Windows on Single GPUs
The bottleneck for long-context agents is memory, not compute. Learn how to implement FP8 or INT8 KV caching to double your context length and survive inference at scale.

The bottleneck for long-context agents is memory, not compute. Learn how to implement FP8 or INT8 KV caching to double your context length and survive inference at scale.

As context windows scale to a million tokens, the KV cache becomes too large for GPU memory. The solution is a multi-tiered cache that offloads data to CPU and NVMe without killing latency.