KV Cache VRAM Calculator: How Much Memory Does Context Length Need? (2026)
This story is from 2026-10-24. It is preserved in the archive; the latest stories are on the live feed.
The KV cache is the memory a transformer uses to remember every token in the context, and its size grows linearly with context length: bytes per token = 2 × layers × KV heads × head dimension × bytes per value. For Qwen3 32B at FP16 that is 256 KiB per token, or about 8 GB for a 32k-token context,…
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- 2026-10-24 13:07 · DEV Community — Machine Learning
KV Cache VRAM Calculator: How Much Memory Does Context Length Need? (2026)