Weights & Biases Pricing in May 2026

Weights & Biases's pricing follows tiered structure: Free Plan for personal use + 100GB storage, Teams at $50/user/month, Enterprise custom-quote starting around $200/user/month. Real-world W&B bills for ML teams land at $200-2,000/month for typical 5-15 person teams; mid-stage ML organizations hit $5K-30K/month.

The Free Plan offer is genuinely valuable for individual ML practitioners. The strategic decision: W&B's value is the breadth of ML workflow coverage: experiment tracking (Runs), dataset versioning (Artifacts), hyperparameter sweeps, model registry, and increasingly LLM-specific features (Weave for LLM observability). For experiment tracking specifically, MLflow is the open-source alternative with strong self-hosting capability — usually preferred for teams who want self-hosted experiment tracking. Comet competes directly with W&B at similar enterprise pricing. Neptune.ai targets similar territory with cleaner UX. ClearML is another open-source alternative. For specifically LLM-observability, LangSmith, Langfuse, Helicone, and Braintrust target this newer niche — W&B Weave competes here. For specifically model-serving and deployment, Modal, Replicate, BentoML, and Triton Inference Server target inference rather than experimentation. For specifically MLOps platforms, Kubeflow, Vertex AI (Google), and SageMaker (AWS) target enterprise MLOps. For dataset-versioning specifically, DVC is the open-source alternative with Git-style data versioning. For specifically ML-model-deployment with monitoring, Arize AI and WhyLabs target ML observability in production. For Hugging Face-anchored teams, Hugging Face Hub plus Spaces handles model and dataset hosting. The W&B vs MLflow vs Neptune decision often splits: W&B for managed enterprise; MLflow for self-hosted; Neptune for cleaner UX.