VRAM Calculator: Estimate Local LLM Requirements
Estimate the VRAM required to run local LLMs like Llama 3 with our interactive calculator. Compare quantization levels like Q4 and Q8 to plan your hardware.
What is the VRAM Calculator?
Running local LLMs requires knowing your hardware limits. I built the VRAM Calculator to help you estimate the video memory needed to run models like Llama 3 and Mistral. Knowing your constraints before downloading a 40GB model saves you hours of frustration.
The Math Behind It
Estimating VRAM is more than just checking the base file size. You have to account for context window length, quantization levels like GGUF Q4 or Q8, and inference engine overhead. The calculator handles the math and gives you a concrete target for your setup.
How It Compares
Static reference tables get outdated fast. This calculator uses dynamic estimates based on real memory footprint data from local AI engines like llama.cpp.
You can use the tool right now: Try the VRAM Calculator.
Ready for Production?
If you are deploying AI agents and need to monitor their execution safely, check out AgentGuard.
FAQ
How much VRAM does a local LLM need?
It depends on parameter count, quant level, context length, and KV cache. An 8B model at Q4_K_M fits about 6 to 8 GB; the calculator estimates your exact case.
Can I run a 70B model on 24GB of VRAM?
A 70B model at Q4 needs roughly 40 GB, so a single 24GB card cannot hold it. Use a smaller model, a lower quant, or split the model across two GPUs.
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Patrick Hughes
Building BMD HODL — a one-person AI-operated holding company. Nashville, Tennessee. Twenty-Two agents.
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