CanIRun.ai
Check if your hardware can run local AI models
Browser-based tool that detects your GPU, CPU, and RAM to show which AI models you can run locally, with performance grades.
What is CanIRun.ai?
A browser-based hardware detection and AI model compatibility checker that scores local model performance against your GPU, CPU, and RAM.
How to use CanIRun.ai?
Open the site in a WebGPU-capable browser, let it read your hardware specs, then browse or filter the model catalog to see which models your machine can run and how well.
Core features of CanIRun.ai
- Browser-based GPU, CPU, RAM, and bandwidth detection via WebGPU
- Compatibility scores and grades (Runs great to Too heavy) for local AI models
- Broad hardware coverage including NVIDIA, AMD Radeon, Apple Silicon, Intel Arc, and mobile SoCs
- Catalog of open models with parameter count, quantization, context, and task filters
- Sortable views by score, size, speed, context, and popularity
- Side-by-side model comparison and tier list views
Target audience of CanIRun.ai
Use cases of CanIRun.ai
- #1Check whether a specific LLM will run on your current GPU before downloading
- #2Pick the best local model for a laptop or workstation within a VRAM budget
- #3Compare GPUs or Apple Silicon chips for AI inference workloads
- #4Estimate quantized model memory requirements across quant levels
- #5Filter the model catalog by task (chat, code, reasoning, vision) and license
CanIRun.ai Details
CanIRun.ai is a browser-based compatibility checker that detects your machine's hardware — GPU, CPU, RAM, and memory bandwidth — and matches it against a catalog of local AI models to predict performance. It assigns a grade from 'Runs great' to 'Too heavy' for each model, factoring in VRAM capacity, memory bandwidth, RAM size, and core count. The catalog covers hundreds of open models across tasks like chat, code, reasoning, and vision, with support for multiple quantizations (Q2_K through F16). Filters let you narrow by GPU family (NVIDIA RTX, Apple Silicon, AMD Radeon, Intel Arc, mobile SoCs), VRAM, RAM, bandwidth, and task type. You can also sort by score, parameter count, speed, context size, or popularity. The site includes a playground, a model compare view, a tier list, and documentation to help users pick the right model for their machine.
CanIRun.ai Pricing
CanIRun.ai Company and Links
FAQ from CanIRun.ai
Does CanIRun.ai need an install?
No, it runs entirely in the browser using WebGPU and browser APIs to read your hardware specs.
Which hardware is supported?
It covers NVIDIA GeForce, RTX PRO, Quadro, Tesla, and data center GPUs, AMD Radeon RX and integrated graphics, Apple Silicon (M1–M5), Intel Arc, and many mobile SoCs including Adreno, Mali, Immortalis, and Raspberry Pi.
How accurate are the compatibility estimates?
The site states that estimates are based on browser APIs and actual specs may vary.
What does the grade mean?
Models are rated from 'Runs great' to 'Too heavy' based on a 0–100 score that weighs VRAM, memory bandwidth, RAM, and cores.
Can I compare two models?
Yes, the site includes a dedicated compare view and a tier list for ranking models on your hardware.
CanIRun.ai Website Traffic Analysis
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Top Keywords
| Keyword | Traffic | Cost Per Click |
|---|---|---|
| can i run ai locally? | 14.3K | -- |
| can i run ai locally | 17.6K | -- |
| can i run ai | 8.7K | -- |
| canirunai | 4.2K | -- |
| canirun.ai | 2.3K | -- |
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