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Comet

comet.com

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Spec score 9.4 #1 of 39 in ML Experiment Tracking Software

What it is

Comet offers two product families on one platform: Opik for observing and evaluating LLM applications and agents, and MLOps for machine-learning workflows. Opik traces execution paths such as context retrieval, model responses and tool calls. Its evaluation tools include test suites, datasets, experiments, LLM-as-a-judge and heuristic metrics. The product lists integrations with more than 40 AI frameworks, model providers and gateways, including LangChain, OpenAI, Google ADK, LangGraph and CrewAI; OpenTelemetry support covers tracking applications in Ruby, Java and other languages. MLOps provides experiment tracking, dataset management, a model registry and production monitoring. Opik's open-source version can be self-hosted, and Enterprise offers flexible deployment options. Free Cloud allows up to 10 team members, 25k spans per month and 60-day data retention. Pro Cloud costs $19 a month and allows up to 50 team members and 100k spans monthly, with the same retention period. MLOps Free is also listed, while MLOps Pro costs $19 per user/month. Enterprise pricing is custom. Comet lists community support for all plans, email support for paid cloud Pro and Enterprise, and dedicated support and SLAs for Enterprise.

Spec sheet

What it does
Comet provides experiment tracking, dataset and model versioning, evaluation, and production monitoring for machine-learning and generative-AI teams.Read 15 Oct 2026 · comet.com
Audience
Comet describes MLOps as designed for teams building and training machine learning models and Opik as suited to applications or agents that make LLM calls.Read 28 Sep 2026 · comet.com
Integrations
Comet advertises integrations with more than 40 AI frameworks, model providers, and gateways, including PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, Hugging Face, LangChain, and OpenAI.Read 15 Oct 2026 · comet.com
Compliance
The Trust Center lists ISO 9001:2015, ISO/IEC 27001:2022, and SOC 2 Type 2 compliance.Read 28 Sep 2026 · trust.comet.com
Support
The pricing page lists community support for all plans, email support for paid cloud Pro and Enterprise, and dedicated support and SLAs for Enterprise.Read 28 Sep 2026 · comet.com
Headquarters
New York City, United StatesRead 23 Sep 2026 · comet.com
Founded
2017Read 23 Sep 2026 · comet.com
Company
Comet says it is headquartered in New York City, has offices in Tel Aviv, and launched in 2017.Read 28 Sep 2026 · comet.com
Changelog
The changelog records updates such as dashboards performance improvements, interactive parallel-coordinates charts, metadata search, and model-registry permission changes.Read 15 Oct 2026 · comet.com
Company facts
Comet ML, Inc. launched in 2017, is headquartered in New York City with offices in Tel Aviv, reports 80 employees in 14 countries, and reports $70 million in funding.Read 15 Oct 2026 · comet.com
Dataset management
Comet versions datasets and links them to experiments for lineage and reproducibility.Read 15 Oct 2026 · comet.com
Documentation
Comet publishes versioned documentation covering installation, REST and Python APIs, integrations, troubleshooting, on-premises configuration, CLI commands, and release notes.Read 15 Oct 2026 · comet.com
Enterprise access
The Enterprise plan lists single sign-on, service accounts, and view-only users.Read 28 Sep 2026 · comet.com
Evaluation
Opik provides test suites, datasets, experiments, and built-in LLM-as-a-judge and heuristic evaluation metrics.Read 28 Sep 2026 · comet.com
Experiment tracking
The platform records and compares machine-learning training runs, metrics, parameters, code, and outputs.Read 15 Oct 2026 · comet.com
Hyperparameter search
Comet includes automated hyperparameter tuning with results tracked in the platform.Read 15 Oct 2026 · comet.com
Legal name
Crunchbase lists the legal name as Comet ML Inc. and the founders as Gideon Mendels and Nimrod Lahav.Read 15 Oct 2026 · crunchbase.com
Licence
The core MLOps platform is closed source; the separate Opik project is released under Apache-2.0.Read 15 Oct 2026 · panoply.io
Limit: G2 reviewers
G2 reviewers report a cluttered learning curve, inconsistent logging discipline, limited language support beyond Python, and costs that rise with seats and usage.Read 15 Oct 2026 · g2.com
Limit: independent review
MakerStack says Comet has a smaller community, restrictive lower-tier storage, basic production monitoring, no built-in hyperparameter sweeps, and still-maturing Opik documentation.Read 15 Oct 2026 · makerstack.co
Limit: Panoply review
Panoply reports UI slowdown at high experiment volume, large-file upload restrictions, SDK-versus-UI inconsistencies, and no bulk export API for historical runs.Read 15 Oct 2026 · panoply.io
LLM evaluations
Opik provides test suites, datasets, and LLM-as-a-judge metrics for evaluating applications.Read 15 Oct 2026 · comet.com
LLM tracing
Opik traces LLM inputs, outputs, metadata, tool calls, and multi-step agent execution.Read 15 Oct 2026 · comet.com
MCP server
Comet provides an MCP server installable with pip or Docker for querying and managing Comet data from AI clients.Read 15 Oct 2026 · comet.com
MLOps
Comet MLOps provides experiment tracking, dataset management, model registry, and model production monitoring.Read 28 Sep 2026 · comet.com
Model registry
The model registry centralizes model versions and supports tracking and deployment workflows.Read 15 Oct 2026 · comet.com
Notable limits
Opik Free Cloud includes up to 10 team members, 25k spans per month, and 60-day data retention; Pro Cloud includes up to 50 team members and 100k spans per month.Read 28 Sep 2026 · comet.com
Notable news: Series B
On November 18, 2021, Comet announced a $50 million Series B led by OpenView with Scale Venture Partners, Trilogy Equity Partners, and Two Sigma Ventures participating.Read 15 Oct 2026 · comet.com
OpenTelemetry
Opik has native OpenTelemetry support for tracking applications in languages including Ruby and Java.Read 15 Oct 2026 · comet.com
Opik
Opik provides LLM observability and evaluation for generative AI applications and agentic systems.Read 28 Sep 2026 · comet.com
Opik product
Opik is Comet's open-source observability and evaluation platform for LLM applications and agents.Read 15 Oct 2026 · comet.com
Praise: G2 reviewers
G2 reviewers repeatedly praise automatic logging, experiment comparison, organized dashboards, and visibility into metrics, parameters, model versions, and outputs.Read 15 Oct 2026 · g2.com
Praise: Gartner reviewers
Gartner reviewers praise straightforward workflow integration, detailed metric tables, original logs, dashboards, and intermediate image outputs.Read 15 Oct 2026 · gartner.com
Praise: TrustRadius reviewers
TrustRadius summarizes praise for Comet's user-friendly interface, broad monitoring and experiment-tracking coverage, visualization dashboard, and easy code integration.Read 15 Oct 2026 · trustradius.com
Production monitoring
Enterprise MLOps includes data-drift detection, feature-distribution analysis, custom SQL metrics, and alerts.Read 15 Oct 2026 · comet.com
Products
Comet says it offers two flagship product families, Opik and MLOps, on the same underlying platform.Read 28 Sep 2026 · comet.com
Prompt tooling
Opik offers prompt versioning, a prompt library, prompt evaluation, and a prompt playground.Read 15 Oct 2026 · comet.com
Public API
Comet documents REST endpoints authenticated with an API key for reading and writing workspace, project, and experiment data.Read 15 Oct 2026 · comet.com
Rating on G2
4.3 out of 5 from 26 reviewsRead 15 Oct 2026 · g2.com
Rating on Gartner Peer Insights
4.8 out of 5 from 4 reviewsRead 15 Oct 2026 · gartner.com
Rating on TrustRadius
8 out of 10 from 1 reviewRead 15 Oct 2026 · trustradius.com
Rating: MakerStack
7.1 out of 10 from the MakerStack editorial reviewRead 15 Oct 2026 · makerstack.co
SDKs
The documented Python SDK installs with pip or conda and exposes experiment, artifact, optimizer, API, and command-line interfaces.Read 15 Oct 2026 · comet.com
Security compliance
Comet's Trust Center lists ISO 9001:2015, ISO/IEC 27001:2022, and SOC 2 Type 2 compliance.Read 15 Oct 2026 · trust.comet.com
Self-hosting
The full Comet platform can be deployed locally or on-premises, while Opik can be downloaded and self-hosted from GitHub.Read 15 Oct 2026 · comet.com
Tracing
Opik traces application execution paths, including context retrieval, model responses, and tool calls.Read 28 Sep 2026 · comet.com
Trust Center controls
The Trust Center describes access control, SSO, incident response, business continuity, continuous monitoring, and data-security practices, with detailed documents available by request.Read 15 Oct 2026 · trust.comet.com

Plans and prices

Free Cloud Free Free plan Up to 10 team members · 25k spans per month · 60-day data retention Read 28 Sep 2026 · comet.com
MLOps Free Free 1 platform user · fair usage · 100GB data · experiment tracking · datasets · model registry Read 15 Oct 2026 · comet.com
Open Source Free Free Full AI observability and agent testing feature set · agent tracing and analysis · test suites and assertions · agent playground Read 28 Sep 2026 · comet.com
Opik Free Cloud Free up to 10 team members · 25,000 spans/month · 60-day retention Read 15 Oct 2026 · comet.com
Opik Open Source Free full Opik feature set · self-hosted Read 15 Oct 2026 · comet.com
MLOps Pro $19 a month per user/month up to 10 users · 1,500 training hours · 500GB storage · $1 per extra training hour · $3 per extra 100GB/month · email support Read 15 Oct 2026 · comet.com
Opik Pro Cloud $19 a month per month up to 50 team members · 100,000 spans/month · customizable retention Read 15 Oct 2026 · comet.com
Pro Cloud $19 a month Per month Up to 50 team members · 100k spans per month · 60-day data retention Read 28 Sep 2026 · comet.com
Enterprise Priced on request Custom Unlimited team members · custom usage plans · flexible deployments · dedicated support and SLAs Read 28 Sep 2026 · comet.com
MLOps Enterprise Priced on request Custom unlimited users · unlimited training hours · flexible deployments · production monitoring · SSO · service accounts · view-only users · dedicated support and SLAs Read 15 Oct 2026 · comet.com
Opik Enterprise Priced on request Custom unlimited team members · custom usage plans · flexible deployments · SSO · dedicated support and SLAs · compliance features Read 15 Oct 2026 · comet.com

Every Comet plan and price →

Strong points and limits

Strong points

  • Opik traces retrieval, model responses and tool calls.
  • Lists integrations with more than 40 AI frameworks and providers.
  • MLOps includes experiment tracking and a model registry.
  • Opik open source can be self-hosted.

Limits

  • Free Cloud is limited to 10 team members.
  • Free Cloud includes 25k spans per month.
  • Cloud plans retain data for 60 days.
  • Enterprise pricing is custom.

Who it suits

Opik suits teams building applications or agents that make LLM calls, while MLOps is designed for teams building and training machine-learning models. Self-hosting is an option for Opik open source; Enterprise lists flexible deployments.

Comet in depth

Read the full write-up

Comet suits teams that need to observe LLM applications, manage model-development work, or both. Its two product families cover distinct workflows, so the right fit depends on which job—and which set of limits—you need.

Overview

Opik handles observability and evaluation for generative AI applications and agents; MLOps covers experiment tracking, dataset management, model registration, and production monitoring. Sharing an underlying platform is useful for organizations working across both disciplines, but it does not mean one plan covers both: Comet prices and caps the product families separately.

Founded in 2017, Comet is headquartered in New York City and has offices in Tel Aviv. API and SDK access and hybrid deployment options make it relevant to teams integrating it into their own environments.

Key features

Opik observability and evaluation

Opik traces context retrieval, model responses, and tool calls, giving teams a way to inspect the steps behind an application's or agent's output. Test suites, datasets, and experiments support structured evaluation; built-in LLM-as-a-judge and heuristic metrics provide ways to assess changes. Its integrations span more than 40 AI frameworks, model providers, and gateways, including LangChain, OpenAI, Google ADK, LangGraph, and CrewAI. OpenTelemetry support extends tracking to AI applications written in Ruby, Java, and other languages.

The open-source Opik version can be self-hosted, while Enterprise offers flexible deployment options. The Trust Center lists ISO 9001:2015, ISO/IEC 27001:2022, and SOC 2 Type 2 compliance, relevant to organizations weighing governance requirements.

MLOps workflow

MLOps combines experiment tracking with dataset management, a model registry, and production monitoring. Run comparison, artifact tracking, and dataset versioning support teams managing training work, while the registry provides a place to manage models. This is the more relevant family for teams building and training machine-learning models; teams focused on LLM application traces should look to Opik instead.

Pricing

Comet is freemium, with separate plans for Opik and MLOps. The free options are useful for small teams or initial workloads, but their user, usage, or retention caps matter as activity grows.

Open Source: free. Includes AI observability and agent testing, agent tracing and analysis, test suites and assertions, and an agent playground. Its self-hosting option suits teams that want to run Opik themselves.

Free Cloud: free. Includes up to 10 team members, 25k spans per month, and 60-day data retention. The span quota and retention period make this a bounded starting tier for cloud use.

MLOps Free: free. Includes 1 platform user, fair usage, and 100GB data usage. Its single-user allowance is best suited to an individual rather than a shared team workflow.

Pro Cloud: $19 a month. Includes up to 50 team members, 100k spans per month, and 60-day data retention. It raises the Free Cloud team and span ceilings but retains the same stated retention period.

MLOps Pro: $19 per user/month. Includes up to 10 users, 1,500 training hours, and 500GB data usage. The per-user charge and training-hour allowance are important budget constraints for teams scaling training work.

Enterprise: custom pricing. Includes unlimited team members, custom usage plans, flexible deployments, dedicated support, and SLAs. Single sign-on, service accounts, and view-only users are also listed for Enterprise.

MLOps Enterprise: custom pricing. Includes unlimited users, unlimited training hours, flexible deployments, dedicated support, and SLAs.

Community support is available across plans; paid cloud Pro and Enterprise add email support, while Enterprise includes dedicated support and SLAs. A free trial is available. The entry pricing starts at 19 /user/mo, but buyers should distinguish MLOps Pro's per-user rate from Pro Cloud's monthly price.

Platforms

Comet supports API, Linux, macOS, self-hosted, web, and Windows. Its API and SDK access and hybrid deployment options suit teams that need to integrate it with existing environments; the self-hosted Opik option is specifically available in the open-source version.

Who it's for

Choose Opik if your application or agent makes LLM calls and you need traces plus repeatable evaluation. Choose MLOps if your team builds and trains machine-learning models and needs experiment, dataset, registry, and production-monitoring workflows. Comet is a sensible candidate for organizations doing both, provided they account for separate plans and quotas. It is a poorer fit for buyers expecting one undifferentiated subscription or usage limits that expand without moving to a higher tier.

Pros and cons

Pro: Opik combines execution tracing with test suites, datasets, experiments, and evaluation metrics, supporting both debugging and repeatable assessment.

Pro: More than 40 integrations and OpenTelemetry support broaden the ways teams can connect AI applications.

Pro: Open-source self-hosting and Enterprise deployment flexibility give teams deployment choices beyond cloud-only use.

Pro: MLOps Free and Opik Free Cloud provide no-cost starting points, with stated user and usage allowances.

Con: Free Cloud is capped at 25k spans per month and 60-day retention; Pro Cloud raises the span cap but not the stated retention period.

Con: MLOps Free allows just one platform user, and MLOps Pro charges per user while capping the plan at 10 users and 1,500 training hours.

Con: Enterprise plans use custom pricing, so teams needing unlimited users or usage must request a tailored plan.

Alternatives

For a broader comparison, see ML Experiment Tracking Software and Model Registry Software.

Weights & Biases is another freemium option with a free plan and trial across API, mobile, desktop, self-hosted, and web platforms. Its free tier specifies five model seats, 5 GB/mo storage, and 1 GB/mo Weave data ingestion; choose it if those stated free-tier allowances better match your needs.

MLRun is a free option with an open-source plan and a separately priced managed offering; choose it if you want to compare those deployment paths.

GitLab Package Registry has a freemium plan whose free tier specifies five users per top-level group, 400 compute minutes/month, and 10 GiB adjustable storage; consider it if those package-registry limits fit your use case.

ClearML offers a freemium model and says its self-hosted version is 100% open source on GitHub; consider it if that self-hosted approach is a priority.

Amazon SageMaker Autopilot is a paid service without a free plan, with pay-as-you-go pricing and no minimum fees or upfront commitments; choose it if usage-based billing suits your budget.

DagsHub has a free Individual plan for public repositories and non-commercial private repositories; consider it if those repository terms match your work.

TensorBoard is a free option; consider it as an alternative.

Trackio is free, including its library and Hugging Face hosting; consider it as an alternative.

Verdict

Comet is a strong fit for teams that need either LLM application observability through Opik or a broader model-development workflow through MLOps, especially when they value both under one platform. Its main draw is the combination of tracing and evaluation or experiment-to-production tooling; look elsewhere if the separate product plans, span and retention caps, per-user MLOps pricing, or custom Enterprise terms do not fit your scale.

Verdict

Comet covers both LLM application observability through Opik and model-development workflows through MLOps. The listed free and Pro Cloud limits, MLOps user allowances and custom Enterprise pricing help distinguish the plan options.

Where Specifiction places it

Alternatives to CometAll alternatives →