Measure BERT model performance using WASM and WebGPU
Evaluate AI-generated results for accuracy
Submit models for evaluation and view leaderboard
Compare audio representation models using benchmark results
Evaluate open LLMs in the languages of LATAM and Spain.
Convert and upload model files for Stable Diffusion
Generate and view leaderboard for LLM evaluations
Display model benchmark results
Browse and submit model evaluations in LLM benchmarks
Browse and submit evaluations for CaselawQA benchmarks
Evaluate and submit AI model results for Frugal AI Challenge
Explore and submit models using the LLM Leaderboard
Convert PaddleOCR models to ONNX format
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.