# Which local AI models will run on your GPU or Mac? > Pick your GPU or Mac and see which of 656 open LLMs run on it, how much VRAM they need at Q4, and what to buy. Source: https://whatcanirunai.vercel.app/ Local AI hardware checker # Will it run on _your_ machine? Pick your GPU or Mac to see which open models fit, or pick a model to see the cheapest hardware that runs it. Estimates at Q4, Q8 and FP16, with speed and power checks. [Plan an AI PC build →](https://whatcanirunai.vercel.app/planner/)[Browse build recipes](https://whatcanirunai.vercel.app/builds/) * **656**open models * **82**GPUs & Macs * **3**quant levels * **Free**JSON API & MCP I have hardwareI want a model Your GPU or MacShow all ### Biggest models that fit on GeForce RTX 3060 12GB [DeepSeek-Coder-V2-Lite-Instruct](https://whatcanirunai.vercel.app/models/deepseek-coder-v2-lite-instruct/)**12.0** / 12.0 GBTight [kanana-1.5-15.7b-a3b-instruct](https://whatcanirunai.vercel.app/models/kanana-1.5-15.7b-a3b-instruct/)**11.9** / 12.0 GBTight [Phi-4-reasoning-vision-15B](https://whatcanirunai.vercel.app/models/phi-4-reasoning-vision-15b/)**11.5** / 12.0 GBTight [Apriel-Nemotron-15b-Thinker](https://whatcanirunai.vercel.app/models/apriel-nemotron-15b-thinker/)**11.4** / 12.0 GBTight [Apriel-1.5-15b-Thinker](https://whatcanirunai.vercel.app/models/apriel-1.5-15b-thinker/)**11.4** / 12.0 GBTight [See all 656 models on this machine](https://whatcanirunai.vercel.app/what-can-i-run/rtx-3060-12gb/) Model you want to runModel page ### Cheapest hardware that fits it at Q4 [Full fit table for this model](https://whatcanirunai.vercel.app/models/qwen3-14b/) [PlannerBuild an AI PC part by partPick GPU, CPU, RAM, PSU and case. Get live VRAM fit, tok/s, PSU and clearance checks, and a share link.Open the planner](https://whatcanirunai.vercel.app/planner/)[Reverse lookupWhat can my rig run?Pick the GPU or Mac you already own (and optional multi-GPU count) to see every model that fits, with tok/s.Check your rig](https://whatcanirunai.vercel.app/what-can-i-run/)[RecipesReady-made buildsPriced part lists for common goals, from a 24 GB budget box to dual 3090s for 70B models.See builds](https://whatcanirunai.vercel.app/builds/) ## Popular checks * [What can I run on GeForce RTX 3060 12GB?](https://whatcanirunai.vercel.app/what-can-i-run/rtx-3060-12gb/)12 GB * [What can I run on GeForce RTX 4090?](https://whatcanirunai.vercel.app/what-can-i-run/rtx-4090/)24 GB * [What can I run on GeForce RTX 3090?](https://whatcanirunai.vercel.app/what-can-i-run/rtx-3090/)24 GB * [What can I run on Radeon RX 7900 XTX?](https://whatcanirunai.vercel.app/what-can-i-run/rx-7900-xtx/)24 GB * [What can I run on Mac mini M6 24GB?](https://whatcanirunai.vercel.app/what-can-i-run/mac-mini-m6-24/)18 GB * [What can I run on Framework Desktop (Ryzen AI Max+ 395) 128GB?](https://whatcanirunai.vercel.app/what-can-i-run/framework-desktop-128/)96 GB ## Popular models * [Qwen3.8-27B](https://whatcanirunai.vercel.app/models/qwen3.8-27b/)\~20.4 GB at Q4 * [Qwen3-14B](https://whatcanirunai.vercel.app/models/qwen3-14b/)\~11.3 GB at Q4 * [gpt-oss-20b](https://whatcanirunai.vercel.app/models/gpt-oss-20b/)\~15.6 GB at Q4 * [Gemma 4 31B](https://whatcanirunai.vercel.app/models/gemma-4-31b-it/)\~22.8 GB at Q4 * [Llama-3.3-70B-Instruct](https://whatcanirunai.vercel.app/models/llama-3.3-70b-instruct/)\~50.2 GB at Q4 * [Qwen3-30B-A3B](https://whatcanirunai.vercel.app/models/qwen3-30b-a3b/)\~22.3 GB at Q4 ## By VRAM size * [Best LLMs for 6 GB VRAM](https://whatcanirunai.vercel.app/best-llm-for/6gb-vram/)198 fit * [Best LLMs for 8 GB VRAM](https://whatcanirunai.vercel.app/best-llm-for/8gb-vram/)315 fit * [Best LLMs for 12 GB VRAM](https://whatcanirunai.vercel.app/best-llm-for/12gb-vram/)350 fit * [Best LLMs for 16 GB VRAM](https://whatcanirunai.vercel.app/best-llm-for/16gb-vram/)388 fit * [Best LLMs for 24 GB VRAM](https://whatcanirunai.vercel.app/best-llm-for/24gb-vram/)423 fit * [Best LLMs for 32 GB VRAM](https://whatcanirunai.vercel.app/best-llm-for/32gb-vram/)504 fit * [All memory sizes](https://whatcanirunai.vercel.app/best-llm-for/)4–128 GB * [VRAM calculator](https://whatcanirunai.vercel.app/vram-calculator/)any size * [How much VRAM do I need?](https://whatcanirunai.vercel.app/how-much-vram/)1B–1T ## Buying guides * [Best GPU for Llama](https://whatcanirunai.vercel.app/best-gpu-for/llama/)3 models * [Best GPU for Qwen3](https://whatcanirunai.vercel.app/best-gpu-for/qwen3/)4 models * [Best GPU for gpt-oss](https://whatcanirunai.vercel.app/best-gpu-for/gpt-oss/)2 models * [Best GPU for DeepSeek R1](https://whatcanirunai.vercel.app/best-gpu-for/deepseek-r1/)4 models * [Best GPU for Gemma 3](https://whatcanirunai.vercel.app/best-gpu-for/gemma-3/)3 models * [Best GPU for Gemma 4](https://whatcanirunai.vercel.app/best-gpu-for/gemma-4/)5 models * [Best GPU for Qwen3.8](https://whatcanirunai.vercel.app/best-gpu-for/qwen3.8/)3 models * [Best GPU for Ornith 1.5](https://whatcanirunai.vercel.app/best-gpu-for/ornith-1.5/)3 models * [Best GPU for Nemotron](https://whatcanirunai.vercel.app/best-gpu-for/nemotron/)3 models * [Best GPU for Liquid AI LFM](https://whatcanirunai.vercel.app/best-gpu-for/liquid-lfm/)2 models * [Best GPU for Mistral](https://whatcanirunai.vercel.app/best-gpu-for/mistral/)4 models * [Best GPU for GLM](https://whatcanirunai.vercel.app/best-gpu-for/glm/)4 models * [Best GPU for Phi](https://whatcanirunai.vercel.app/best-gpu-for/phi/)4 models * [Best GPU for long-memory models](https://whatcanirunai.vercel.app/best-gpu-for/memory-models/)3 models * [Best GPU for local coding models](https://whatcanirunai.vercel.app/best-gpu-for/coding-models/)8 models * [Best GPU for local LLMs](https://whatcanirunai.vercel.app/best-gpu-for-local-llm/)every card ranked * [Best Mac for local LLMs](https://whatcanirunai.vercel.app/best-mac-for-local-llm/)Mac mini to Mac Studio * [Best mini PC for local LLMs](https://whatcanirunai.vercel.app/best-mini-pc-for-local-llm/)Mac mini, Framework, DGX Spark * [Best used GPU for local LLMs](https://whatcanirunai.vercel.app/best-used-gpu-for-local-llm/)RTX 3090, P40, MI50, A6000 * [Best AMD GPU for local LLMs](https://whatcanirunai.vercel.app/best-amd-gpu-for-local-llm/)Radeon and ROCm support * [Best Intel GPU for local LLMs](https://whatcanirunai.vercel.app/best-intel-gpu-for-local-llm/)Arc B580, Pro B70, A770 * [NVIDIA vs AMD vs Mac](https://whatcanirunai.vercel.app/nvidia-vs-amd-vs-mac/)which platform to buy * [Tokens per second](https://whatcanirunai.vercel.app/tokens-per-second/)how fast it runs * [Multi-GPU for local LLMs](https://whatcanirunai.vercel.app/multi-gpu-for-local-llm/)dual GPU vs one card * [Q4 vs Q8 vs FP16](https://whatcanirunai.vercel.app/quantization/)which quant to run * [Context length and VRAM](https://whatcanirunai.vercel.app/context-length/)8k to 128k memory * [Ollama VRAM requirements](https://whatcanirunai.vercel.app/ollama-vram-requirements/)memory per Ollama tag * [GGUF VRAM requirements](https://whatcanirunai.vercel.app/gguf-vram-requirements/)Q3\_K\_M to Q8\_0 sizes * [MoE vs dense models](https://whatcanirunai.vercel.app/moe-vs-dense/)memory vs speed * [GPU power consumption](https://whatcanirunai.vercel.app/gpu-power-consumption/)watts and cost per token * [Best GPU by budget](https://whatcanirunai.vercel.app/best-gpu-under/)$300–$3,500 * [GPU vs GPU comparisons](https://whatcanirunai.vercel.app/compare/)head-to-head ## Just added * [LongCat-2.5](https://whatcanirunai.vercel.app/models/longcat-2.5/)\~1241.8 GB at Q4 * [NorthCUA-Pro](https://whatcanirunai.vercel.app/models/northcua-pro/)\~277.6 GB at Q4 * [ERNIE-5.5-Flash-Base](https://whatcanirunai.vercel.app/models/ernie-5.5-flash-base/)\~200.6 GB at Q4 * [Apex-35B-V1.0](https://whatcanirunai.vercel.app/models/apex-35b-v1.0/)\~26.1 GB at Q4 * [NorthCUA-Mini](https://whatcanirunai.vercel.app/models/northcua-mini/)\~25.5 GB at Q4 * [Clover-35B-A3B-Preview](https://whatcanirunai.vercel.app/models/clover-35b-a3b-preview/)\~25.2 GB at Q4 * [Arete-27B](https://whatcanirunai.vercel.app/models/arete-27b/)\~20.1 GB at Q4 * [Groot-19B-A3B-261023](https://whatcanirunai.vercel.app/models/groot-19b-a3b-261023/)\~14.5 GB at Q4 --- Agent guide: https://whatcanirunai.vercel.app/llms.txt · JSON API: https://whatcanirunai.vercel.app/developers/