CanIRun.ai

CanIRun.ai is a free web tool that lets you instantly check which open-source AI models are compatible with your local hardware. By selecting your GPU or Apple Silicon chip, it calculates VRAM usage, estimated inference speed (tokens/second), and assigns a runability score to hundreds of models. The tool covers models from Meta, Mistral, Google, Alibaba, DeepSeek, and more, with support for multiple quantization formats (Q2_K through F16/GGUF).

• Hardware compatibility checker: Select your GPU (NVIDIA, AMD, Intel, Apple Silicon, Qualcomm, etc.) or set custom VRAM/bandwidth values to see which models fit your machine.
• Runability scoring: Each model receives a score (0–100) and a grade (Runs great / Runs well / Decent / Tight fit / Barely runs / Too heavy) based on your hardware profile.
• Quantization format breakdown: View estimated file sizes and quality retention for Q2_K, Q3_K_M, Q4_K_M, Q5_K_M, Q6_K, Q8_0, and F16 formats for every model.
• Model filtering and sorting: Filter by task (chat, code, reasoning, vision), provider, license, and architecture (Dense/MoE); sort by score, parameter count, context length, speed, or VRAM.
• Model comparison: Use the compare feature to evaluate multiple models side-by-side across hardware profiles.
• Tier list: Browse a ranked tier list of models to quickly identify the best options for your hardware class.
• Educational docs: Built-in documentation explains parameters, quantization, VRAM, MoE architecture, context length, tokens/second, GGUF format, and memory bandwidth.
• Data sourced from llama.cpp, Ollama, and LM Studio: Model data is kept up to date and reflects real-world local inference tooling.