Comet
An ML experiment tracking and LLM observability platform for building, monitoring, and evaluating AI models.
Best for
Teams needing both ML experiment tracking and LLM/agent observability in one connected platform.
Skip if
You only need a simple standalone experiment tracker and don't need LLM observability.
What is Comet?
Comet is an AI developer platform covering two connected needs: traditional ML experiment tracking and management, and LLM and agent observability through its Opik product. On the MLOps side, it lets data scientists track and compare training runs, version models and datasets, and monitor production models, with support for frameworks like PyTorch, TensorFlow, Hugging Face, and scikit-learn. Opik, Comet's LLM observability and evaluation platform, adds tracing across 60+ integrations, automatic error detection with an AI assistant called Ollie that recommends fixes, test suites with LLM-as-a-judge evaluation, and production monitoring dashboards, including cost tracking for coding agents like Claude Code. Opik's core feature set is available as a free, self-hostable open-source download in addition to Comet's hosted cloud plans.
SpecificationsAI-estimated
Key Features of Comet
Use Cases for Comet
ML experiment comparison
Track and compare multiple training runs to identify which hyperparameters produced the best model.
LLM application debugging
Use Opik's tracing to see exactly what an AI agent did step-by-step and diagnose why it failed.
Automated LLM evaluation
Run LLM-as-a-judge test suites against new prompts or models before deploying changes.
AI coding agent cost tracking
Monitor spend on coding agents like Claude Code through Opik's cost intelligence dashboards.
Pros & Cons of Comet
Pros
- Covers both classic ML experiment tracking and modern LLM and agent observability under one company.
- Opik's open-source option gives teams a genuinely free, self-hosted path with the full feature set.
- Broad framework support (PyTorch, TensorFlow, Hugging Face, scikit-learn) for the MLOps side.
- Cost intelligence for coding agents like Claude Code is a distinctive feature for teams managing AI spend.
Cons
- Having two related but distinct products, classic MLOps and Opik, can be confusing when first evaluating the platform.
- Free cloud tiers cap data volume, such as 25k spans/month, requiring a paid plan for production-scale usage.
- Enterprise features like SSO and compliance certifications are reserved for the custom-priced Enterprise tier.
Frequently Asked Questions
Is Comet free to use?
Yes, Comet offers a free cloud tier for both its MLOps product and Opik, and Opik's core feature set can also be self-hosted for free as open source.
What is Opik?
Opik is Comet's LLM observability and evaluation platform, covering tracing, error detection, test suites, and production monitoring for AI applications and agents.
Does Comet support LLM-as-a-judge evaluation?
Yes, Opik includes test suites and evaluations that use LLM-as-a-judge metrics to score AI application outputs.
What frameworks does the MLOps side support?
It supports common frameworks including PyTorch, TensorFlow, Hugging Face, and scikit-learn.
Pricing Overview
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