# OpenAI Agents SDK Alternatives (2026): 5 Compared

> Source: https://theagentsindex.com/openai-agents-sdk/alternatives (curated, quality-gated, re-verified)

The OpenAI Agents SDK is the fastest way to ship a straightforward agent: four primitives — agents, handoffs, guardrails and sessions — MIT-licensed, free, and provider-agnostic across 100-plus models via LiteLLM despite the OpenAI branding, with tracing built in from day one. Its own listing is equally direct about where that minimalism runs out: durable state is limited to `RunState`, a snapshot you capture manually after a run pauses for human approval, not automatic step-by-step checkpointing, and handoffs are linear chains rather than a graph — its own "not for" call names "teams needing complex branching workflows, automatic step-by-step checkpointed state or compliance-grade audit trails" outright. The five tools below are independently researched, Published listings on this site, not a scraped or AI-generated list: each carries current pricing we verified against the vendor's own page, sourced pros and cons, and an honest "best for" and "not for" call. LangChain (with LangGraph) is the most direct fix for OpenAI's own admitted branching-and-checkpointing gap; CrewAI gets to a working multi-agent crew faster if the job is coordination, not deep control; Pydantic AI answers the same durability question with real checkpointed execution since its 2.0 release; and Mastra and Letta each fix it from a different angle still — one is the only TypeScript-native entrant in the category, the other is the only one built stateful from the ground up.

| # | Name | What it is | Why it's here | Pricing | API |
| --- | --- | --- | --- | --- | --- |
| 1 | [LangChain](https://theagentsindex.com/langchain.md) | The most widely-used framework for building LLM apps and agents, with LangGraph for stateful multi-agent control: open-source and free to self-host. | The most direct fix for OpenAI Agents SDK's own admitted gap: LangGraph adds a real graph engine — deterministic, node-level branching and state control — where OpenAI's SDK only snapshots RunState manually at human-approval pauses. The cost is trading four primitives for a much larger ecosystem, with a real (if now-stabilized, post-1.0-GA) learning curve LangChain's own listing admits to. | Free | Yes |
| 2 | [CrewAI](https://theagentsindex.com/crewai.md) | Open-source Python framework for role-based multi-agent crews, with a hosted build and runtime that adds enterprise governance, native SDKs for the major LLMs, and Ollama via LiteLLM. | A faster path to a working multi-agent crew than OpenAI's own agents-and-handoffs pattern, if the job is role-based coordination rather than deep branching control — CrewAI's crew abstraction gets a team of specialists running in fewer lines. The trade-off: CrewAI's own managed AMP platform jumps straight from a 50-execution free tier to a custom Enterprise sales conversation, with nothing publicly priced in between. | Free (month (50 workflow executions)) | Yes |
| 3 | [Pydantic AI](https://theagentsindex.com/pydantic-ai.md) | The Python AI SDK for type-safe agents, realtime voice, image generation and embeddings, with every model a string swap away. | Answers OpenAI Agents SDK's own durability gap directly: since its backwards-incompatible 2.0 release (2026-06-23), Pydantic AI wires into Temporal, DBOS, Prefect or Restate for real checkpointed, resumable execution — well past OpenAI's own manual RunState snapshots. The cost is operating that separate orchestrator yourself, and OpenAI's SDK ships an official TypeScript SDK where Pydantic AI is Python-only. | Free | — |
| 4 | [Mastra](https://theagentsindex.com/mastra.md) | The TypeScript-native agent framework. Agents, durable workflows, memory and observability in one Apache 2.0 package, with an optional managed cloud platform. | Not a lighter OpenAI SDK — a different ecosystem entirely: the only framework in this category built TypeScript-first rather than Python-first with a JS port, unifying agents, durable typed workflows and memory in one Apache-2.0 package. The trade-off is a much younger ecosystem (26.5K GitHub stars) and its deepest enterprise controls sit behind a separate source-available licence, not the open core. | Free | Yes |
| 5 | [Letta](https://theagentsindex.com/letta.md) | Letta is the open-source framework behind Letta Code, a stateful coding agent whose memory, skills, and identity persist across sessions rather than rebuilding context on every call. | Fixes a different limitation than checkpointing: OpenAI's Sessions persist conversation history per thread, but Letta agents are stateful, durable server objects whose memory, tools and identity persist across every run instead of resetting between sessions. The cost is a much smaller ecosystem (23.9K+ GitHub stars) and a single, smaller seed round behind it. | $0 / month | Yes |

## Methodology

We drew every alternative from this site's own Published, individually-researched frameworks category — seven listings in total, the same corpus behind the site's own framework decision guide (LangChain vs CrewAI vs LlamaIndex vs AutoGen vs Pydantic AI vs OpenAI Agents SDK vs Mastra vs Letta) — rather than compiling a fresh, unverified list. A tool qualifies only if it is a genuine standalone agent-building framework we have already fact-checked against its own pricing and licence page, with sourced pros, cons and a "best for" call in place, and if it answers a real, specific gap OpenAI's own SDK names about itself rather than duplicating another entry's angle. Microsoft AutoGen sits in the same category but was excluded on the facts already in its own listing — the same reasoning this site's LangChain alternatives page already applied: AutoGen is in Microsoft's own stated maintenance mode, its README pointing new users to the Microsoft Agent Framework instead, not a tool we'd recommend adopting fresh over an actively-developed SDK today. LlamaIndex was excluded for the reason its own FAQ gives: it is retrieval-first and frequently paired WITH an orchestration framework in production, not a substitute for one. The order below runs from the closest fix for OpenAI's own admitted branching-and-checkpointing gap, through a faster path to the same multi-agent goal, through a different durability answer, to the two different-axis entrants — language ecosystem, then statefulness.