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RUNLOCALAI · v38
Glossary / Hardware & infrastructure / VRAM (Video RAM)
Hardware & infrastructure

VRAM (Video RAM)

VRAM is the dedicated memory on a GPU. For local AI, VRAM capacity is the single most important spec — it determines which models you can load. The relationship between model size, quantization, and VRAM is the central calculation behind every "will this run" question.

Rules of thumb: a model in FP16 needs about 2GB per billion parameters; in Q4 about 0.6 GB per billion. Add 15-30% overhead for KV cache, activation memory, and runtime buffers. A 7B model in Q4 fits comfortably in 8 GB VRAM; 70B Q4 needs 48 GB; 70B FP16 needs 140 GB.

Important: VRAM is gated, not just slow. If a model spills into system RAM via CPU offload, generation drops from 40 tok/s to 2-3 tok/s — a usability cliff. Apple Silicon's unified memory bypasses this distinction, treating all RAM as VRAM, which is why M-series Macs punch above their weight for local LLMs.

Related terms

QuantizationCPU OffloadVRAM Bandwidth

See also

hardware: rtx-5080hardware: rtx-4090hardware: apple-m4-max
Buyer guides
  • Best GPU for local AI →
  • 16 GB vs 24 GB VRAM →
When it doesn't work
  • CUDA out of memory →
  • WSL out of memory →
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  • RTX 3090 vs RTX 5080 (24 vs 16 GB) →
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  • RTX 3090 (24 GB used) →