Determine GPU requirements for large language models
View and submit LLM benchmark evaluations
Measure BERT model performance using WASM and WebGPU
Submit deepfake detection models for evaluation
Evaluate LLM over-refusal rates with OR-Bench
Convert PyTorch models to waifu2x-ios format
Push a ML model to Hugging Face Hub
Browse and submit language model benchmarks
Request model evaluation on COCO val 2017 dataset
Optimize and train foundation models using IBM's FMS
View and submit language model evaluations
Upload ML model to Hugging Face Hub
View and submit machine learning model evaluations
Can You Run It? LLM version is a specialized tool designed to help users determine the GPU requirements for running large language models (LLMs). It provides detailed insights into whether your hardware can support specific AI models, ensuring optimal performance and compatibility.
• GPU Compatibility Check: Quickly determine if your GPU can run popular LLMs.
• Performance Prediction: Estimate inference speed and memory usage for different models.
• Customizable Settings: Adjust parameters like batch size and sequence length to match your workflow.
• Benchmarking: Compare your GPU's performance against others in similar setups.
• Model Compatibility: Check support for the latest LLMs, including those from major frameworks.
• AI-Powered Recommendations: Get suggestions for upgrading or optimizing your hardware.
What GPUs are supported by Can You Run It? LLM version?
The tool supports a wide range of NVIDIA and AMD GPUs, with regular updates to include the latest models.
Is the performance prediction accurate?
The predictions are based on extensive benchmarks and real-world data, ensuring high accuracy for typical use cases.
Can I use this tool for models outside the supported list?
While the tool is optimized for popular LLMs, you can input custom model specifications for compatibility checks. Results may vary.