LangChain vs ZenML
On the evidence we track, LangChain leads this comparison with a composite score of 79/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for mlops & llmops tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
LangChain
LeaderA unified developer platform consisting of open-source frameworks and commercial tools for building, testing, monitoring, and deploying AI agents and LLM-powered applications.
ZenML
ZenML is a Python-based orchestration framework that manages machine learning pipelines and agents across any infrastructure, from local development to production Kubernetes clusters. It provides centralized artifact management, automated tracking and versioning, and enterprise-grade security compliance for reproducible AI systems.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
LangChain
LeaderFree Developer plan. Plus plan from $39/user/mo with unlimited seats. Enterprise custom pricing billed annually.
- DeveloperFree
- 1 free seat
- 5000 base traces per month
- Full LangSmith access
- Plus$39/seat/month, unlimited seats, 10k traces/month included
- Unlimited seats
- 10000 base traces per month
- 1 free small serverless deployment
- Team collaboration
- LangSmith Deployment service access
- EnterpriseContact sales
- Advanced administration options
- Enhanced security controls
- Priority support
- Custom deployment options
ZenML
Free open-source version; managed Pro service available
- CommunityFree
- experiment tracking
- pipeline orchestration
- artifact storage
- model versioning
- ProManaged service pricing not specified
- managed control plane
- governance
- SSO
- SLA support
- audit trails
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
- OpenAI
- AWS
LangChain
Leader- Anthropic
- Cohere
- Azure OpenAI
- Azure AI Search
- Microsoft Fabric
- Azure Kubernetes Service
- OpaquePrompts
- MCP (Model Context Protocol)
ZenML
- Git
- GitHub
- GitLab
- Kubernetes
- Docker
- Poetry
- Slack
- ClickUp
- MLflow
- Databricks
- Trackio
- LangGraph
- PyTorch
- scikit-learn
- Hugging Face
- LlamaIndex
- PyTorch Lightning
- Axolotl
- AzureML
- Google Cloud
- Azure
- DigitalOcean
- Kubeflow
- MySQL
LangChain or ZenML: which one depends on you
A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.
Free to run, no account needed to start. How the evaluation works
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.