Honest pros, cons, and verdict on this ml & llm observability tool
✅ Covers both classical ML and LLM observability — one platform across the stack
Starting Price
Free
Free Tier
Yes
Category
ML & LLM Observability
Skill Level
Developer
End-to-end ML and LLM observability platform spanning experiment tracking, model registry, evaluation, and production monitoring.
Comet is a long-standing ML platform that has evolved into a unified observability layer for both classical ML and modern LLM applications. The platform spans the full lifecycle: Experiment Management tracks every training run with hyperparameters, metrics, code, data, and reproducible artifacts; the Model Registry catalogs trained models with lineage and approvals; Production Monitoring watches deployed models for drift, degradation, and data quality issues; and Opik (Comet's open-source LLM evaluation tool) provides LLM-specific tracing, evals, prompt management, and a playground. Opik is notable for being fully open source under Apache 2.0 with a hosted cloud option, giving teams a way to instrument LLM apps without sending traces to a closed platform. Engineering and research teams use Comet to keep dozens or hundreds of concurrent experiments organized, share results with stakeholders via reports, and avoid the classic 'which run produced this model?' problem. For LLM applications, Opik tracks every prompt and completion, scores outputs with code-based or LLM-as-judge evaluators, and helps catch regressions before they reach users. Comet has been around long enough to integrate with every major ML framework (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face, LangChain, LlamaIndex). Pricing offers a free tier for individuals, a paid Team tier, and Enterprise plans with on-prem deployment options.
per month
per month
Comet delivers on its promises as a ml & llm observability tool. While it has some limitations, the benefits outweigh the drawbacks for most users in its target market.
End-to-end ML and LLM observability platform spanning experiment tracking, model registry, evaluation, and production monitoring.
Yes, Comet is good for ml & llm observability work. Users particularly appreciate covers both classical ml and llm observability — one platform across the stack. However, keep in mind older ui in some sections compared to llm-native competitors like langfuse or braintrust.
Yes, Comet offers a free tier. However, premium features unlock additional functionality for professional users.
Comet is best for Tracking and comparing ML training runs and Open-source LLM observability with Opik. It's particularly useful for ml & llm observability professionals who need advanced features.
There are several ml & llm observability tools available. Compare features, pricing, and user reviews to find the best option for your needs.
Last verified March 2026