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Machine Learning · head to head

LangChain vs Ray

LangChain logo

LangChain

Machine Learning

Build applications with LLMs through composability

From
Free
Rated
-
Full reviewWebsite
Ray logo

Ray

Machine Learning

Scale AI and Python applications

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: LangChain the free Developer plan of LangSmith is limited to 1 seat; Ray windows support is beta and multi node Ray clusters are untested on Windows
  • They diverge on capability: LangChain covers Chains and agents, Ray covers Distributed computing.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which LangChain and Ray actually diverge.

Attributes where LangChain and Ray differ
AttributeLangChainRay
Founded20222019

Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), platforms (Linux, Mac, Windows), 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 LangChain

  • Chains and agents
  • Retrieval-augmented generation
  • Memory management
  • Tool integration
  • Prompt templates
  • OpenAI
  • Anthropic
  • Pinecone

Only in Ray

  • Distributed computing
  • Ray Train
  • Ray Tune
  • RLlib
  • Ray Serve
  • PyTorch
  • TensorFlow
  • scikit-learn

Both cover

  • Hugging Face
  • Linux support
  • Mac support
  • Windows support

What people use each for

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

LangChain

  • Building LLM applications and agents in Python or JavaScriptnot Ray
  • Tracing and debugging LLM chains and agent runsnot Ray
  • Evaluating prompt and model changes against datasetsnot Ray

Ray

  • Distributed AI model training and servingnot LangChain
  • Large-scale data processingnot LangChain
  • Reinforcement learning workloadsnot LangChain
  • ML inference servingnot LangChain

Where each one falls short

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

LangChain

  • The free Developer plan of LangSmith is limited to 1 seat
  • Base traces are retained for 14 days only; 400 day retention costs extra
  • Included traces are capped at 5,000 per month on Developer and 10,000 per month on Plus, with everything beyond billed pay as you go
  • Self hosted and hybrid deployment of LangSmith is Enterprise only
  • Custom SSO, RBAC and ABAC are Enterprise only
  • A support SLA is Enterprise only
  • Enterprise pricing is by quote with no published rate

Ray

  • Windows support is beta and multi node Ray clusters are untested on Windows
  • Windows lacks copy on write forking, which raises memory requirements, and Ray code assumes UNIX filenames
  • Multi node clusters are untested on Apple Silicon Macs
  • The Java API is experimental and community supported only, and requires matching Java and Python versions
  • Python 3.13 support is beta

Pricing, plan by plan

LangChain

Free
  • Open SourceFree
    • Full framework
    • Community support
  • LangSmith$39/month
    • Debugging
    • Monitoring
    • Testing

Ray

Free
  • Open SourceFree
    • Full Ray framework
    • All libraries
    • Community support
  • Anyscale PlatformFree
    • Managed infrastructure
    • Enterprise support
    • SLAs

Which should you pick?

Choose LangChain if

  • You need chains and agents.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want retrieval-augmented generation.
LangChain review

Choose Ray if

  • You need distributed computing.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want ray train.
Ray review

Questions people ask

Is LangChain or Ray better?
Neither clearly leads. LangChain starts at Free and Ray at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, LangChain or Ray?
LangChain starts at Free and Ray at Free.
Does LangChain or Ray run on more platforms?
Both run on Linux, Mac, Windows, so platform support will not decide this one for you.
Can I use LangChain for free?
Both have a free tier, so you can try either at no cost before committing.
What is LangChain best used for?
LangChain is most often used for building llm applications and agents in python or javascript, tracing and debugging llm chains and agent runs, evaluating prompt and model changes against datasets. Of those, building llm applications and agents in python or javascript and tracing and debugging llm chains and agent runs are not what Ray is typically brought in for.
What can LangChain do that Ray cannot?
LangChain covers Chains and agents, Retrieval-augmented generation, Memory management, Tool integration. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib. Both handle Hugging Face, Linux support, Mac support, Windows support.

Answered from the vendors’ own pages

LangChain: Does LangChain charge for its services?

LangChain's main website does not display pricing. However, LangSmith (a related platform) offers both free and paid plans. Visit the dedicated pricing page or contact LangChain for details.

Source
Ray: Is Ray free?

Yes. Ray is free and open source software with over 34,800 GitHub stars and 1,000+ contributors. Users can download and use the Ray framework at no cost.

Source
LangChain: How can I learn about LangChain pricing?

Click on the Pricing link in navigation or use the Try LangSmith or Get a demo options to explore pricing for LangChain's commercial offerings.

Source
Ray: Is there a paid option for Ray?

Yes. Anyscale, the managed platform built by Ray's creators, offers paid tiers with enterprise features like governance and advanced tooling. Specific Anyscale pricing details are not listed on the Ray website.

Source
Ray: Can I try Ray with credits?

Yes. New users can try Ray with $100 credit on Anyscale's managed platform to explore the service.

Source
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