Comet ML vs Neptune.ai
MLOps pricing comparison · 2026
Comet ML pricing ranges from $0–$19/undefined, while Neptune.ai ranges from $150–$250/undefined. Comet ML is typically 96% more affordable, though your actual cost depends on tier and team size.
Comet ML and Neptune.ai are both experiment tracking and MLOps platforms designed to help data science teams log, visualize, and compare ML experiments. They occupy a similar niche — between the free open-source tools like MLflow and the enterprise-scale platforms like Weights & Biases — but differ in their pricing models, feature depth, and target audience.
Comet ML is one of the older players in the experiment tracking space, offering a free tier for individuals and open-source teams, with paid plans starting at $19/mo. It provides solid experiment comparison, model registry, and production monitoring features. Neptune.ai is a more recent platform with a stronger focus on metadata management for the entire ML lifecycle — not just experiments but also datasets, models, and custom metadata schemas — with plans starting at $150/mo for teams.
The pricing gap is notable: Neptune.ai's team plans ($150–$250/mo) position it as a mid-tier managed service, while Comet's $19/mo starting price makes it accessible for small teams. Both platforms integrate with major ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost) and support custom dashboards and artifact tracking, but Neptune.ai's metadata management depth and query capabilities tend to appeal more to mature ML teams with complex versioning needs.
Plan-by-Plan Pricing
| Plan | Comet ML | Neptune.ai |
|---|---|---|
| Free | Free /user/month | $150 /per user/month |
| Pro | $19 /user/month | $250 /per user/month |
| Enterprise | Custom | Custom |
Our Verdict
Choose Comet ML if you're a small team or individual practitioner looking for affordable experiment tracking with a solid feature set. It's ideal for teams that need a step up from MLflow without paying Neptune.ai's higher starting price. Comet's free tier is one of the more generous in the space.
Choose Neptune.ai if your team needs rich metadata management across the full ML lifecycle — not just experiment runs but datasets, models, and custom schema tracking. It's best for mature ML teams or organizations with complex model versioning requirements who can justify the higher price point for improved query and collaboration features.
Frequently Asked Questions
01 Is Comet ML cheaper than Neptune.ai?
Yes. Comet ML has a free tier for individuals and paid plans starting at $19/mo. Neptune.ai's team plans start at $150/mo and go up to $250/mo, making it 8–13x more expensive than Comet's entry paid tier. Both have enterprise pricing available on request.
02 Which is better for tracking custom metadata and artifacts?
Neptune.ai has a stronger metadata management system, designed around a flexible schema that lets you log and query arbitrary objects — experiments, datasets, model checkpoints, custom metadata — in a unified interface. Comet ML handles standard experiment metadata well but Neptune.ai's query capabilities for complex metadata hierarchies are more advanced.
03 Can Comet ML replace Neptune.ai for an ML team?
For most experiment tracking use cases, Comet ML is a capable Neptune.ai alternative at a lower price. The main trade-off is Neptune.ai's deeper metadata management and its ability to track non-experiment objects (datasets, models, etc.) in the same interface. Teams with simple experiment tracking needs will find Comet ML fully sufficient.