About LLM RAM Calculator
Calculate memory requirements for running large language models. Compare different quantization levels and check GPU compatibility.
Frequently Asked Questions
How much VRAM do I need to run an LLM?
It depends on the model size and quantization. A 7B parameter model needs ~14GB at FP16, ~7GB at INT8, or ~3.5GB at INT4. Larger models scale proportionally.
What is quantization?
Quantization reduces model precision to save memory. FP16 uses 16 bits per parameter, INT8 uses 8 bits, INT4 uses 4 bits. Lower precision saves memory with minimal quality loss.
Can I run LLMs on consumer GPUs?
Yes! With INT4 quantization, many models fit on consumer GPUs. A 7B model at INT4 needs ~4GB VRAM. 13B models need ~8GB. Use tools like llama.cpp, GGML, or GPTQ.
What about Apple Silicon Macs?
Apple Silicon uses unified memory (shared between CPU and GPU). A 16GB M1 can run 7B models, 32GB handles 13B, and 64GB+ handles 30B+ models.