LangChain vs Groq

LangChain

Groq

LangChain · 18 features

• Agents — Tool-using agents with reasoning loops.
• Chains (LCEL) — LangChain Expression Language — pipe primitives into chains.
• Checkpointers (LangGraph) — Persist agent state to SQL, Mongo, Redis, Postgres.
• Document Loaders — 150+ loaders for PDF, HTML, Notion, Google Drive, S3, GitHub, etc.
• Human-in-the-loop — Pause agent for approval, then resume.
• LangGraph — Stateful graph-based agent runtime. Durable, replayable, human-in-the-loop.
• LangGraph Platform — Managed hosting for LangGraph agents with state persistence.
• LangGraph Studio — Desktop IDE for debugging agent graphs.
• LangServe — Deploy chains as FastAPI endpoints.
• Memory — Buffer, summary, entity, vector memory stores.
• Output Parsers — Structured JSON, Pydantic schemas, function calling.
• Prompt Templates — Templating + partial filling + output parsers.
• RAG (Retrieval-Augmented Generation) — Standard patterns + 50+ retrievers.
• Streaming — First-class streaming at every layer.
• Subgraphs — Compose agent graphs hierarchically.
• Text Splitters — Recursive, token, semantic splitters for chunking.
• Tools — 400+ pre-built tools (web search, code, databases, APIs).
• Vector Store Integrations — 60+ vector DBs (Pinecone, Chroma, Weaviate, PGVector, Qdrant, Milvus).

Groq · 7 features

• Audio Transcription — Whisper endpoint.
• Batch API — 50% discount.
• Chat Completions (OpenAI-compat) — Standard /v1/chat/completions endpoint.
• Function Calling
• JSON Mode — Enforce JSON output format.
• Prompt Caching — 50% discount on cached input.
• Streaming — SSE streaming for chat.