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Head-to-head · LLM Application Development Frameworks

LangChain vs Spring AI

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score LangChain #1 in LLM Application Development Frameworks 9.4/10 Free plan Free plan✓ 0 of 5 features Visit LangChain
Spring AI #4 in LLM Application Development Frameworks 9.0/10 Free plan Free plan✓ 3 of 5 features Visit Spring AI

LangChain leads on 0 checks, Spring AI on 3, and 1 is even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreLangChain · 9.4/10
  • Free planboth
  • Most featuresSpring AI · 3 of 5

LangChain scores higher on our rubric for llm application development frameworks: 9.4 against 9.0 out of 10; our editors rank them #1 and #4.

Spring AI offers rag support; LangChain doesn't publish it. Spring AI offers agent and tool use; LangChain doesn't publish it. Spring AI offers prompt optimization; LangChain doesn't publish it.

LangChain is the better fit for general-purpose LLM app and agent development. Spring AI is the better fit for java teams building RAG and AI applications.

  • LangChain fits best

    General-purpose LLM app and agent development

  • Spring AI fits best

    Java teams building RAG and AI applications

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. How we rank.

Side by side

Feature LangChain 9.4/10 Visit ↗ Spring AI 9.0/10 Visit ↗
At a glance
Editor score 9.4 9.0
Ranking #1 in LLM Application Development Frameworks #4 in LLM Application Development Frameworks
Best for General-purpose LLM app and agent development Java teams building RAG and AI applications
Pricing model Free Free
Starting price Not published Not published
Free plan ✓ ✓
Free trial — —
Deployment Self-hosted Self-hosted
Support Community, Docs Docs, Community
Integrations 1,000+ integrations 16 integrations
Built for Solo, Small business, Mid-market, Enterprise Small business, Mid-market, Enterprise
Features LangChain 0/5 · Spring AI 3/5
RAG support Not published ✓ (best)
Agent and tool use Not published ✓ (best)
Workflow graphs Not published Not published
Prompt optimization Not published ✓ (best)
JavaScript/TypeScript SDK Not published Not published
Specs
Primary language Not published Java
Open-source license Not published Apache-2.0
Our review
Pros
  • Connects applications to a broad range of models, tools, databases, and data sources
  • Provides document-processing and retrieval components for RAG workflows
  • Supports human approval and durable agent execution through LangGraph
  • Portable APIs cover multiple model providers and synchronous or streaming use.
  • RAG advisors, document ETL, evaluation, and observability support end-to-end workflows.
  • Connects to a broad range of model providers and vector stores.
Cons
  • Requires developers to run it in their own application environment
  • Its broad set of abstractions may exceed the needs of a narrowly scoped app
  • Tracing, evaluation, and deployment workflows are associated with separate LangSmith
  • Java and Spring focus makes it less suited to teams using other application stacks.
  • Self-hosted deployment puts application operation on the adopting team.
  • Framework code requires developers to assemble and maintain the application.
Our verdict

LangChain is an open-source framework for developers building LLM applications and agents. It is aimed at a wide range of project sizes, from solo developers to enterprise teams, and runs self-hosted in application code. Its scope covers…

Read the review →

Spring AI is an open-source Java framework for building AI-powered applications in the Spring ecosystem. It is aimed at teams that want to connect models, enterprise data, and application APIs while keeping model-provider implementations…

Read the review →
  1. LangChainLLM Application Development Frameworks 9.4Free plan
  2. Spring AILLM Application Development Frameworks 9.0Free plan

Strengths and trade-offs

  • LangChain — where it wins

    • Connects applications to a broad range of models, tools, databases, and data sources
    • Provides document-processing and retrieval components for RAG workflows
    • Supports human approval and durable agent execution through LangGraph

    Where it doesn't

    • Requires developers to run it in their own application environment
    • Its broad set of abstractions may exceed the needs of a narrowly scoped app
    • Tracing, evaluation, and deployment workflows are associated with separate LangSmith

  • Spring AI — where it wins

    • Portable APIs cover multiple model providers and synchronous or streaming use.
    • RAG advisors, document ETL, evaluation, and observability support end-to-end workflows.
    • Connects to a broad range of model providers and vector stores.

    Where it doesn't

    • Java and Spring focus makes it less suited to teams using other application stacks.
    • Self-hosted deployment puts application operation on the adopting team.
    • Framework code requires developers to assemble and maintain the application.

More comparisons

All LLM application development frameworks comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update