DevOps & Infrastructure

LLM Hardware & VRAM Sizing Calculator

Plan your model hosting topology. Calculate GPU VRAM allocations for model weights and dynamic KV-caches under configurable user concurrency limits.

Architecture Settings

Select a model preset or configure manual parameters to estimate VRAM usage.

Model Architecture Preset

Model Weight Precision (Quantization)

Concurrent Request Batch Size 16 requests Number of simultaneous chat/inference user streams.

Target Context Length (Sequence Length) 8,192 tokens

Model Weights RAM 0 GB Static VRAM footprint

KV Cache Size 0 GB Dynamic stream allocation

Total Required VRAM 0 GB Includes 20% system buffer

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Adjust variables to see matching server architectures.

Topology Setup -

Hardware Memory Pool -

The estimation is derived from standard GPU serving equations:

Weights Size: Weight Memory = Parameters (B) × Bytes-per-Weight × 1.2 (CUDA Overhead)
KV Cache (GQA) Size: KV Cache Memory = 2 × Layers × KV-Heads × Head-Dimension × 2 (FP16 Bytes) × Batch × Sequence-Length