LuminaBench
Compare AI models across creative, coding, and reasoning tasks
Prepare, train, evaluate, and operate machine-learning systems.
Compare AI models across creative, coding, and reasoning tasks
Post-train and serve AI models across different accelerators
Ask typed questions and receive structured model decisions
A small local decision model for routing and triage
Route AI tasks to models through one shared interface
Train a private decision model from your team’s past work
Train specialized AI models from your agents’ production data
Train reusable image models from a focused set of reference images
Build and operate custom AI systems with specialist engineering teams
Manage datasets and build computer vision applications
Prepare training datasets with AI labels and human review
Simulate realistic users to test voice and chat agents
Evaluate voice AI conversations and identify where systems need improvement.
Browser-based robot demonstrations and training data for physical AI
Compare computer-use agents through live tasks, recorded attempts, and human preferences.
Prepare data, configure model training, evaluate checkpoints, and ship through one CLI.
Compare prompts across models and keep evaluation results in your browser workspace.
Explore preserved answers from AI models across shared questions.
Find recurring AI agent failures and investigate production traces
Source training datasets and custom collections for robotics and physical AI