Local LLM VRAM Calculator
Estimate the video memory required to load and run a local large language model based on parameter count, quantization and context length.
Runs locally in your browser
Includes model weights, a rough KV-cache allowance for your context length, and runtime overhead. Leave 1–2 GB extra headroom for the OS and other apps.
What is the Local LLM VRAM Calculator?
This tool estimates how much GPU memory a local LLM needs to load its weights plus a working allowance for the KV cache at a given context length. It performs arithmetic only and does not run or call any model.
How to use it
- 1Enter the model size in billions of parameters.
- 2Choose a quantization (bits per weight).
- 3Set your context length.
- 4Read the estimated VRAM requirement.
How it works
Weight memory = parameters × bits / 8. A KV-cache allowance scales with context length and model size, and a fixed overhead is added for activations and the runtime.
Limitations & notes
- Real usage varies by runtime (llama.cpp, vLLM, Transformers) and settings.
- Estimates assume a single GPU; multi-GPU splitting changes the picture.
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