
CanIRun.ai is a browser-based hardware analyzer that instantly tells you whether your machine can run popular open-source AI and large language models (LLMs). Without installing any software or sharing your files, it scans your CPU, GPU, RAM, and storage from within the browser, then matches your specs against real model requirements. Designed for developers, AI enthusiasts, and data scientists, CanIRun.ai removes the guesswork from local model deployment. Instead of digging through documentation, GitHub issues, and forum threads, you get clear guidance on which models are compatible, what quantization levels might work, and where your system may hit bottlenecks. CanIRun.ai focuses on privacy-friendly, client-side checks: your hardware information is analyzed locally and does not require backend access to your data. With a growing catalog of open-source models and LLM frameworks, it helps you decide whether to run models on your own machine, upgrade hardware, or switch to a smaller architecture. Whether you tinker with LLaMA-based models, run RAG pipelines, or test experimental checkpoints, CanIRun.ai gives you a fast, free, and accurate readiness check right in your browser—before you spend time downloading multi-gigabyte models or configuring complex environments.
Check if your laptop can run a specific open-source LLM before downloading tens of gigabytes of model files.
Validate whether your current GPU VRAM is enough for 4-bit or 8-bit quantized models in your local RAG or chatbot project.
Quickly assess a new development machine or server to see what size models your team can realistically host in-house.
Compare multiple machines in your lab to decide which one is best suited for fine-tuning or high-throughput inference.
Use during hardware planning to estimate if an upgrade is needed to support upcoming AI workloads and frameworks.