Neptune.ai vs OpenAI API

Yes. Neptune can be self-hosted on a Kubernetes cluster with ClickHouse, MySQL, and Redis dependencies, allowing organizations to maintain full data control.

API inputs and outputs are not used for training by default, which differs from the consumer product. Retention periods and enterprise terms change, so read the current data usage policy rather than trusting a summary.

Neptune integrates with PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Hugging Face Transformers, and Optuna for hyperparameter optimization.

No. The weights are not distributed. If self-hosting is a requirement, you are looking at open-weight models instead, with the operational and quality trade-offs that implies.

Neptune's Team plan costs $49 per user per month, resulting in $490/month for 10 users, comparable to Weights and Biases at $50/user.

Per token, with input and output priced differently and each model priced differently. Batch processing and cached input prefixes reduce it. The practical consequence is that your bill is a function of prompt design, not just of request count.

Neptune.ai is shutting down its external SaaS service on March 5, 2026, following its acquisition by OpenAI in December 2025. Customers must export and migrate data before that date.

The same model family delivered by Microsoft under an Azure contract, with Azure identity, networking and regional controls, and a different release cadence for new models. Enterprises with an Azure agreement often choose it for procurement and data residency reasons rather than technical ones.

Cap input length, cache repeated prefixes, route easy requests to smaller models, use the batch path where latency does not matter, and set per-user limits before launch rather than after the first surprising invoice.