Weights & Biases Models

Automate hyperparameter search and optimization to find the best-performing configurations without manually managing every experiment. Choose from Bayesian optimization, grid search, or random search, customize parameter distributions and search logic, and use early stopping to focus compute on the most promising runs. Track progress, logs, and visualizations in one shared workspace so every result is transparent, reproducible, and easy to compare.

Reports help you document findings from AI experiments and turn results into clear, shareable narratives for teammates and stakeholders. Combine live visualizations, data, and commentary in one place to communicate progress, gather feedback, and plan next steps. Reports update automatically as new results arrive, making it easy to compare projects, establish benchmarks, and keep everyone aligned.

Track GPU, CPU, memory, network, and other system metrics alongside model performance to identify bottlenecks, improve hardware utilization, and control training costs. Prebuilt integrations with platforms such as NVIDIA eliminate the need to configure system metrics logging manually.

When training on CoreWeave’s industry-leading infrastructure, events from Mission Control appear directly within your W&B workspace, contextualized to the relevant training runs. Review timelines, GPU errors, network timeouts, service bottlenecks, and remediation guidance in one place to troubleshoot issues faster and optimize training and fine-tuning workloads.