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LangChain vs Groq

Compare LangChain and Groq on deployment, pricing, model support, and more.

LangChain

Tagline
Open-source LLM application framework — chains, agents, RAG, and 700+ integrations with 127K GitHub stars
Description
LangChain is the most widely used open-source framework for building LLM-powered applications. It provides composable abstractions for chains (sequencing LLM calls), agents (tool-using AI that can browse, run code, and call APIs), and RAG (retrieval-augmented generation with 700+ data and tool integrations). Available in Python and JavaScript, with LangSmith for observability and LangGraph for complex multi-agent workflows.
Category
LLM Frameworks
Pricing
Free
Metric
139,957 GitHub stars (source)
Link
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Groq

Tagline
Ultra-fast LLM inference API — run Llama, Mixtral, and Gemma at 500+ tokens/second on custom LPU hardware
Description
Groq is a cloud inference provider running popular open-source LLMs (Llama, Mixtral, Gemma) on their custom Language Processing Unit (LPU) hardware, achieving 500-800+ tokens/second — dramatically faster than GPU-based inference. With a free tier and OpenAI-compatible API, Groq is widely used for building low-latency AI applications, real-time agents, and prototyping with open models without managing infrastructure.
Category
LLM Frameworks
Pricing
Freemium
Metric
Link
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