Weights & Biases.
Experiment tracking and evals — the AI-ops standard for fine-tuning and training.
What it is.
Experiment-tracking platform for ML and AI teams. Acquired by CoreWeave in 2025 and bundled into CoreWeave's AI-compute stack. The de-facto standard for fine-tuning workflows — every major Llama and Mistral fine-tune at Fortune 500 buyers passes through a W&B dashboard.
Where it fits.
Teams running fine-tuning, RLHF, or evaluation at scale. CoreWeave integration makes it the natural choice for GPU workloads on CoreWeave's compute. Stronger on training-side observability than LangSmith; weaker on agent-trace surface.
- Industry-standard for ML experiment tracking
- Native CoreWeave integration for GPU workloads
- Strong dataset and model registry features
- Agent-trace UX behind LangSmith
- CoreWeave acquisition raised lock-in concerns for some buyers
Frequently asked.
How did the CoreWeave acquisition change W&B?
Tighter integration with CoreWeave compute. No documented changes to the open-source SDK or the multi-cloud roadmap, though some non-CoreWeave buyers are watching.
Is W&B suitable for agent observability?
Possible but not the strongest fit. Agent traces are LangSmith territory; W&B owns training and evaluation.
Can W&B be self-hosted?
Yes. Enterprise tier supports self-hosted deployment, including air-gapped environments.
