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This page helps you understand how LangChain Deep Agents compare to the Claude Agent SDK and the Codex SDK.
Deep Agents is used in production by OpenSWE and LangSmith Fleet.

Overview

Key differences

LangChain Deep Agents:
  • Model flexibility: Swap model providers (Anthropic, OpenAI, or 100+ others) at any time and run evaluations.
  • Long-term memory: Persist context across sessions and threads with the Memory Store
  • Sandbox-as-tool pattern: Run individual operations in isolated sandboxes from different providers while the agent runs outside, or run the full agent inside a sandbox
  • Virtual filesystem: Use pluggable backends (in-memory, disk, durable stores, sandboxes) for context and checkpoint management
  • Production deployment: Deploy via LangSmith or self-host with the Agent Server
  • Observability: Use LangSmith for native tracing and debugging
Claude Agent SDK:
  • Standardize on Claude: First-class support for Claude models across Anthropic, Azure, Vertex AI, and AWS Bedrock
  • Custom hosting: Build your own HTTP/WebSocket layer and run the SDK in containers
  • Hooks: Easily intercept and control agent behavior
Codex SDK:
  • Standardize on OpenAI: GPT-5.3-Codex and OpenAI-specific tooling
  • OS-level sandbox modes: Use built-in read-only, workspace-write, or danger-full-access modes
  • MCP server mode: Expose your agent as an MCP server with codex mcp-server
  • Observability: Use OpenAI Traces

Feature comparison

Notice a mistake?

We drafted this comparison on March 4th, 2026. If you notice mistakes or changes in products, please file an issue.