tech calculator
LLM Quantization VRAM & Perplexity Estimator
Estimate LLM serving memory footprint, factoring in model parameters, quantization precision, system overhead, and KV cache size.
Inputs
Model Configuration
KV Cache & Context
Results
Total Serving VRAM
49.37 GB
Recommended GPU Setup
1x A100 (80GB) or H100 (80GB) or 2x L40S (48GB)
Formula
LLM Quantization VRAM formula
VRAM = (Parameters × Bits / 8 × 1.2) + KV_Cache + OverheadCalculates serving memory using model parameter weights and dynamic KV cache parameters.
Step by step
How the calculation works
- 1Enter the model parameter count in billions (e.g. 70 for LLaMA-3-70B).
- 2Select weight quantization precision (bits per parameter). Lower bits reduce VRAM but increase perplexity.
- 3Enter the sequence length (context window) and concurrent batch size.
- 4Specify layer count, attention heads, and GQA (Grouped Query Attention) ratio.
- 5Review the recommended GPU configuration based on the total serving memory footprint.
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