Run Local AI - free tool from

Does it run locally?

Pick your graphics card, Mac or mini PC, or let us detect it. See which LLMs, image, video and decision models fit in memory, and how fast they should run.

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Everything you need to pick hardware for local AI

LLMs 536 language models Image models 47 diffusion models Video models 34 video models Decision models 63 System One models Hardware 284 GPU, Mac and AI-chip profiles Apps 39 apps for Mac, PC, Linux My hardware Detect it, get a full report Compare Two GPUs or Macs, side by side

Model Finder

Can your GPU or Mac run it?

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How the estimate works

Three numbers decide it

01 · MemoryDoes it fit?Model weights at each quantization, plus the KV cache for your context length and runtime overhead, against the memory your GPU or Mac can actually give a model.
02 · BandwidthHow fast will it answer?Generating each token reads the weights once, so tokens per second follow memory bandwidth. Mixture-of-experts models only read their active experts.
03 · QualityIs it the best that fits?A curated quality tier for each model carries most of the score, so the top pick is the best model that fits, not the smallest one.

Example

Llama 3.3 70B on a 128 GB Mac

At Q6_K it needs about 69 GB. A Mac with 128 GB of unified memory lets a model use about 96 GB, so it fits, at roughly 6 tokens per second.

See the full breakdown

Popular checks

What people ask

68Good quality (B) · 68 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking.Llama 3.3 70B Instructon Apple M4 Max (128 GB) · Fits in memory72Great quality (A) · 72 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking.Qwen3 32Bon NVIDIA GeForce RTX 3090 · Tight fit70Great quality (A) · 70 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.gpt-oss 20Bon NVIDIA GeForce RTX 4060 Ti 16GB · Fits in memory78Great quality (A) · 78 of 100: how capable the model is at FP8, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking.FLUX.1 [dev]on NVIDIA GeForce RTX 4060 · Tight fit60Good quality (B) · 60 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking.Gemma 3 27B ITon NVIDIA GeForce RTX 4070 Ti SUPER · Tight fit77Great quality (A) · 77 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.DeepSeek R1 (671B)on Apple M3 Ultra (512 GB) · Tight fit

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