LocalOps is a free hardware compatibility engine for local AI inference. Stop guessing if your GPU can run a model — just check. Select your GPU and any model (LLaMA, Mistral, Phi, Gemma, Qwen and 488 more) and instantly get VRAM requirements across 20 quantization levels, plus speed estimates. Covers 144 GPUs, 492 models. No sign-up. No fluff.

Framer — Launch websites with enterprise needs at startup speeds.

Launch websites with enterprise needs at startup speeds.

LocalOps started from a simple frustration: I was spending more time guessing whether a model would run on my GPU than actually building with it. Running AI locally sounds great — privacy, speed, control — but in reality, it’s messy. Will this model fit in VRAM? What quantization do I need? How much RAM is enough? Is it even worth trying on my setup? So I built LocalOps to answer one core question instantly: “Can my hardware run this model — and how well?” Instead of digging through Reddit threads, GitHub issues, and scattered benchmarks, you get a structured compatibility engine that maps GPUs to models with practical insights. This launch is just the beginning. I’d love your feedback: What hardware are you running? What models are you struggling with? What would make this 10x more useful? If you run models locally — this is for you.

Framer — Launch websites with enterprise needs at startup speeds.

Launch websites with enterprise needs at startup speeds.

LocalOps

Can your GPU run AI models? Local inference VRAM calculator

Can your GPU run AI models? Local inference VRAM calculator