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Machine Learning · head to head

Langwatch vs ClearML

Langwatch logo

Langwatch

Machine Learning

LLM engineering platform for testing and evaluating AI agents in production

From
Free
Rated
-
Full reviewWebsite
ClearML logo

ClearML

Machine Learning

Open-source MLOps platform for experiment tracking and orchestration

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Langwatch free plan limited to 50k events per month, restricting larger deployments; ClearML broad scope means more to learn and more to run than a focused tracking tool
  • They diverge on capability: Langwatch covers Agent simulation testing, ClearML covers Experiment tracking.

Where they differ

Only the attributes on which Langwatch and ClearML actually diverge.

Attributes where Langwatch and ClearML differ
AttributeLangwatchClearML
Pricing modelTiered subscription with usage-based overage chargesOpen-source self-hosted, with paid hosted and enterprise tiers
PlatformsWeb, Docker, KubernetesLinux, macOS, Windows, Docker, Kubernetes

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Langwatch

  • Agent simulation testing
  • LLM evaluation
  • OpenTelemetry tracing
  • Langy AI Engineer
  • Governance controls
  • Multiple deployment options
  • Framework support

Only in ClearML

  • Experiment tracking
  • Remote execution
  • Data versioning
  • Pipelines

What people use each for

The jobs each tool is most often brought in to do.

Langwatch

  • Continuous testing of AI agents before production deploymentnot ClearML
  • Automated test creation from product requirementsnot ClearML
  • LLM response quality evaluation and scoringnot ClearML
  • Production agent monitoring and cost trackingnot ClearML
  • Governance and access control for AI systemsnot ClearML

ClearML

  • Tracking experiments across a team so results are reproduciblenot Langwatch
  • Moving training from laptops to shared GPU hardware without repackagingnot Langwatch
  • Versioning datasets alongside the experiments that consumed themnot Langwatch

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Langwatch

  • Free plan limited to 50k events per month, restricting larger deployments
  • Pricing in EUR may complicate budgeting for US-based teams
  • Usage-based overage model can create unpredictable costs
  • Self-hosted option requires DevOps expertise

ClearML

  • Broad scope means more to learn and more to run than a focused tracking tool
  • Self-hosting the server is real infrastructure — database, file storage and web server
  • Documentation quality is uneven across the newer parts of the platform
  • Smaller community than the most popular tracking tools, so fewer worked examples exist

Pricing, plan by plan

Langwatch

Free
  • DeveloperFree
    • 50k events per month
    • 14-day data access
    • 2 users
  • Growth$29/month
    • 200k events per month included
    • 5 EUR per 100k additional events
    • 30-day data retention
  • Enterprise$undefined/custom
    • Custom event limits
    • Hybrid, self-hosted or on-premises deployment
    • Custom SSO and RBAC

ClearML

Free
  • Open sourceFree
    • Experiment tracking
    • Pipelines
    • Self-hosted server

Which should you pick?

Choose Langwatch if

  • You need agent simulation testing.
  • You want to start without paying.
  • You work on Web, Docker, Kubernetes.
  • You also want llm evaluation.
Langwatch review

Choose ClearML if

  • You need experiment tracking.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes.
  • You also want remote execution.
ClearML review

Questions people ask

Is Langwatch or ClearML better?
Neither clearly leads. Langwatch starts at Free and ClearML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Langwatch or ClearML?
Langwatch starts at Free and ClearML at Free.
Does Langwatch or ClearML run on more platforms?
Langwatch runs on Web, Docker, Kubernetes. ClearML runs on Linux, macOS, Windows, Docker, Kubernetes.
Can I use Langwatch for free?
Both have a free tier, so you can try either at no cost before committing.
What is Langwatch best used for?
Langwatch is most often used for continuous testing of ai agents before production deployment, automated test creation from product requirements, llm response quality evaluation and scoring, production agent monitoring and cost tracking. Of those, continuous testing of ai agents before production deployment and automated test creation from product requirements are not what ClearML is typically brought in for.
What can Langwatch do that ClearML cannot?
Langwatch covers Agent simulation testing, LLM evaluation, OpenTelemetry tracing, Langy AI Engineer. ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines.

Answered from the vendors’ own pages

Langwatch: Is there a permanent free tier?

Yes, Langwatch's Developer plan is free forever with 50k events per month, 14-day data access, 2 users, and no credit card required. It is specifically designed for individual developers prototyping AI applications.

Source
ClearML: Is ClearML free?

The open-source version is free and self-hostable. Hosted and enterprise tiers are paid.

Langwatch: What is Langy and how does it save time?

Langy is an AI-powered tool that automates test creation. It converts product requirements into test scenarios, runs simulations, scores results, and generates pull requests with fixes in a median of 14 minutes.

Source
ClearML: How much code does tracking require?

Very little — adding a couple of lines to an existing training script captures parameters, metrics and environment automatically.

Langwatch: What frameworks does Langwatch support?

Langwatch works with LangGraph, LangChain, CrewAI, OpenAI Agents, AWS Bedrock, Azure OpenAI, Vertex AI, and other major LLM frameworks and platforms.

Source
ClearML: Does ClearML replace MLflow?

It covers MLflow’s tracking and adds orchestration, remote execution and data versioning. Whether that breadth is an advantage or extra weight depends on whether you need the rest.

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