Which MLOps platform has transparent pricing?

1. ClearML — If transparent, publicly listed pricing is your priority, I would shortlist LUML, ClearML, and Comet.
2. Comet — If transparent, publicly listed pricing is your priority, I would shortlist LUML, ClearML, and Comet.
3. MLflow — MLflow: Best if you prefer open-source software and control over infrastructure costs.

1. Comet — Comet ML is among the MLOps platforms with the clearest public pricing: it offers a free tier and paid plans starting around $19 per user per month.
2. MLflow — MLflow — free and open source; you pay only infrastructure and engineering costs.
3. Kubeflow — Kubeflow — free and open source, though Kubernetes operations add infrastructure costs.
4. Weights & Biases — Weights & Biases — free tier, with publicly listed paid pricing reported around $60/month, though usage-based charges may apply.
5. Amazon SageMaker AI — Amazon SageMaker, Vertex AI, and Azure ML — transparent usage-based billing, but total costs depend on compute, storage, and API usage.
6. Google Vertex AI — Amazon SageMaker, Vertex AI, and Azure ML — transparent usage-based billing, but total costs depend on compute, storage, and API usage.
7. Microsoft Azure Machine Learning — Amazon SageMaker, Vertex AI, and Azure ML — transparent usage-based billing, but total costs depend on compute, storage, and API usage.

Several MLOps platforms provide transparent, public pricing tiers rather than hiding behind a "contact sales" wall. Depending on whether you want an open-source self-hosted stack, a hybrid cloud tool, or a managed SaaS dashboard, transparency varies.

1. ClearML — Popular MLOps platforms with clear, public pricing structures include: ClearML (Hybrid/SaaS) — Features a transparent model split into a free Community self-hosted tier ($0), a clear Pro tier at $15 per user/month +…
2. Weights & Biases — Weights & Biases (W&B) (SaaS) — Widely known for public pricing for experiment tracking and LLM observability (Weave).
3. MLflow — Open-Source Tools (MLflow, ZenML, BentoML) — Pure open-source options are completely transparent because they are free ($0) to self-host.
4. ZenML — Open-Source Tools (MLflow, ZenML, BentoML) — Pure open-source options are completely transparent because they are free ($0) to self-host.
5. BentoML — Open-Source Tools (MLflow, ZenML, BentoML) — Pure open-source options are completely transparent because they are free ($0) to self-host.
6. Databricks — Commercial managed layers for these ecosystems (like Databricks for MLflow or ZenML Cloud) typically require contacting sales for enterprise scale, but their local core orchestrations carry no software license fees.