Measure BERT model performance using WASM and WebGPU
View and submit language model evaluations
Find and download models from Hugging Face
Calculate memory needed to train AI models
Display model benchmark results
Generate and view leaderboard for LLM evaluations
Browse and filter ML model leaderboard data
Download a TriplaneGaussian model checkpoint
Calculate GPU requirements for running LLMs
Explore and submit models using the LLM Leaderboard
SolidityBench Leaderboard
Calculate VRAM requirements for LLM models
Display leaderboard for earthquake intent classification models
The WebGPU Embedding Benchmark is a tool designed to measure the performance of BERT models using WebAssembly (WASM) and WebGPU. It provides a platform to evaluate and compare the efficiency of embedding models across different hardware and software configurations. This benchmark is particularly useful for developers and researchers looking to optimize machine learning workloads in web-based environments.
What is the difference between WebGL and WebGPU?
WebGPU is the successor to WebGL, offering improved performance and better support for modern GPUs. WebGPU provides more efficient memory management and faster computation for machine learning tasks.
Which browsers support WebGPU?
As of now, WebGPU is supported in Chrome, Edge, and Safari Technology Preview. Ensure your browser is up-to-date to run the benchmark effectively.
How can I ensure consistent benchmark results?
To achieve consistent results, run the benchmark in a controlled environment with minimal background processes. Ensure the system's GPU is not under heavy load from other applications.