Announcing the Ollama GPU Calculator
If you have spent any time running local models with Ollama, you already know the awkward part: picking a model is easy; knowing whether your GPU can actually host it is not. Parameter count, quantization, context length, and VRAM interact in ways that are hard to eyeball — especially once you start mixing cards or looking at Apple Silicon unified memory.
I built the Ollama GPU Compatibility Calculator to answer that question up front. You pick a model size, quantization, context length, and one or more GPUs, and it estimates VRAM / memory demand, rough tokens-per-second, and whether the configuration looks compatible, borderline, or insufficient. It is the same kind of sizing tool I have shipped for VDI over the years — this time aimed at local LLM hardware.
Who it is for
Anyone sizing a local Ollama setup: hobbyists deciding whether a laptop GPU is enough, engineers comparing consumer RTX cards before a purchase, and teams planning multi-GPU or Apple Silicon boxes for private models. If you are tired of discovering “out of memory” only after a long model pull, this is for you.
Why it helps
Guessing from a model card is a poor substitute for a calculator. Context length alone can dominate VRAM. Quantization changes the math. Multi-GPU setups do not scale linearly. The calculator makes those trade-offs visible before you commit time, disk, or budget — and it is open source, so you can inspect the assumptions and improve them.
How to try it
Use the live tool here: aleibovici.github.io/ollama-gpu-calculator.
Source, issues, and contributions live on GitHub: github.com/aleibovici/ollama-gpu-calculator.
I also posted the original announcement on Reddit for the Ollama community: r/ollama — Ollama GPU Compatibility Calculator.
If you find a wrong GPU entry, a bad estimate, or a model family that needs better defaults, open an issue or a PR. Feedback from people who run these boxes day to day is what keeps a calculator honest.
Thanks — and enjoy sizing before you pull.
– André