hermes-agent vs LangChain Rust

Side-by-side comparison of two AI agent tools

Short answer

  • LangChain Rust has had no commit in 17 months; hermes-agent is actively maintained (33,428 commits in the last 90 days).
  • hermes-agent is growing faster: +5,710 GitHub stars in the last 30 days vs +13 for LangChain Rust.
  • Pick hermes-agent for: the agent that grows with you. Pick LangChain Rust for: langChain for Rust, the easiest way to write LLM-based programs in Rust.

From GitHub data refreshed daily.

h
hermes-agentopen-source

The agent that grows with you

LangChain Rustopen-source

🦜️🔗LangChain for Rust, the easiest way to write LLM-based programs in Rust

Metrics

hermes-agentLangChain Rust
Stars250.9k1.3k
Star velocity /mo5.7k13.105263157894738
Commits (90d)33.4k0
Releases (6m)100
Overall score0.9465511756357280.20114322752134345

Pros

    • +Supports multiple LLM providers (OpenAI, Claude, Ollama) with consistent API
    • +Comprehensive vector store integrations including Postgres, Qdrant, and SurrealDB
    • +Native Rust performance and memory safety for production AI applications

    Cons

      • -Smaller ecosystem and community compared to Python LangChain
      • -Requires Rust knowledge which has a steeper learning curve
      • -Documentation and examples are more limited than the main LangChain project

      Use Cases

        • •Building RAG systems with vector databases for semantic document retrieval
        • •Creating conversational AI applications with persistent memory and context
        • •Developing high-performance AI pipelines that require Rust's safety and speed
        View hermes-agent DetailsView LangChain Rust Details

        FAQ

        Which is more popular, hermes-agent or LangChain Rust?
        hermes-agent has more GitHub stars (250,877 vs 1,348).
        Which is more actively developed, hermes-agent or LangChain Rust?
        hermes-agent had more commits in the last 90 days (33,428 vs 0).
        Should I use hermes-agent or LangChain Rust?
        Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.