DeepAgents vs LangGraph

Side-by-side comparison of features, pricing, and ratings

Analysis generated Live tool data as of 2026-11-08
Cross-checked through our multi-step verification ·
Saved

DeepAgents or LangGraph: which should you choose?

DimensionDeepAgentsLangGraph
PricingFreeFree · from $39/seat/mo
Best forDevelopers who want sub-agents, filesystem, and human oversight pre-assembled, Teams building long-horizon, multi-step agent workflows that outgrow one context windowBackend and platform engineers shipping stateful agents to production, Teams that need human approval gates inside an agent loop
Standout featuresSub-agents that delegate tasks to agents with isolated context windows · Pluggable filesystem: read, write, edit, and search over local, sandboxed, or remote backends · Context management that summarizes long threads and offloads tool output to diskGraph-based state management for explicit agent control flow · Human-in-the-loop checks to steer and approve agent actions · Built-in memory storing conversation history and context across sessions
Viability score82/10081/100
APIYesYes

DeepAgents is the stronger pick for developers who want sub-agents, filesystem, and human oversight pre-assembled; LangGraph fits better for backend and platform engineers shipping stateful agents to production.

Built from live tool data, last verified 2026-11-08.

DeepAgents
DeepAgents

DeepAgents is an open-source agent harness for long-horizon, multi-step agents with sub-agents and a pluggable filesystem.

Visit Website
LangGraph
LangGraph

LangGraph is a low-level agent orchestration framework for building stateful, controllable AI agents as graphs.

Visit Website
Pricing
Free
Freemium
Plans
Open SourceFree
DeveloperFree
Plus$39/seat/mo
EnterpriseCustom
Popularity
6.1k views
3.1k views
Skill Level
Advanced
Advanced
API Available
Platforms
APICLI
API
Categories
🕸️ Agent Frameworks & Orchestration
🕸️ Agent Frameworks & Orchestration📡 LLM Observability & Evals
FeaturesDeepAgentsLangGraph
Sub-agents that delegate tasks to agents with isolated context windows
Pluggable filesystem: read, write, edit, and search over local, sandboxed, or remote backends
Context management that summarizes long threads and offloads tool output to disk
Shell access: run commands in your sandbox of choice
Human-in-the-loop: approve, edit, or reject tool calls before they run
Persistent memory via pluggable state and store backends for cross-session recall
Skills: reusable behaviors the agent loads on demand
Bring your own functions or connect any MCP server as tools
Model-agnostic: works with any LLM that supports tool calling
Frontier, open-weight, and local model support (Ollama, vLLM, llama.cpp, Baseten, Fireworks)
Built on LangGraph with streaming, persistence, and checkpointing
Tracing, evaluation, and deployment via LangSmith
Deep Agents Code: pre-built terminal coding agent installed with one curl command
Python library installed with uv add deepagents
JavaScript/TypeScript library via deepagents.js
Graph-based state management for explicit agent control flow
Human-in-the-loop checks to steer and approve agent actions
Built-in memory storing conversation history and context across sessions
First-class token-by-token streaming of reasoning and actions
Single-agent, multi-agent, and hierarchical architectures in one framework
Low-level primitives for fully customizable agent design
Model-agnostic: build and ship with any model provider
MCP support in the open-source stack, including elicitation and the stateless protocol
Agent runtime for orchestrating long-running agent workflows
MIT-licensed open-source library, free to use
IntegrationsDeepAgentsLangGraph
LangGraph
LangSmith
MCP servers
OpenAI
Anthropic
Google
Ollama
vLLM
llama.cpp
Baseten
Fireworks
Google Gemini
OpenRouter
Azure
AWS Bedrock
HuggingFace

Frequently Asked Questions

Which is better, DeepAgents or LangGraph?

The best choice between DeepAgents and LangGraph depends on your specific use case — we compare them independently on features, current pricing, integrations, and real-world signals (with an on-demand sentiment scan available for each). See the side-by-side breakdown above to match them to your needs.

What are the main differences between DeepAgents and LangGraph?

The key differences include pricing model, feature set, platform support, and skill level requirements. Review the full comparison on RightAIChoice for a detailed breakdown.

Is there a free version of DeepAgents or LangGraph?

Check the pricing section in the comparison for the latest pricing details on both tools, including free tiers, trial options, and paid plans.

What else are DeepAgents and LangGraph compared with?

CrewAI vs DeepAgents comparison
Langfuse vs LangGraph comparison
Haystack vs LangGraph comparison
LangGraph vs Vercel AI SDK comparison
LangGraph vs CrewAI vs AutoGen comparison
LangGraph vs Semantic Kernel comparison

Where can you read more about DeepAgents and LangGraph?

DeepAgents
View DeepAgents reviewDeepAgents alternatives
LangGraph
View LangGraph reviewLangGraph alternatives

Browse these categories

Best AI Agent Frameworks & Orchestration toolsBest AI LLM Observability & Evals tools
Still deciding? Get the weekly AI tools brief

One email a week — new tools, honest comparisons, no spam.

Analysis generated by our model pipeline from live data: