If you are choosing a multi-agent framework in mid-2026, the good news is that the shortlist finally stopped moving. Three options reached stable, production-labeled releases, and they cover the field: Microsoft Agent Framework 1.0, LangGraph 1.2, and the OpenAI Agents SDK. The bad news is that every comparison table you'll find lines them up on features — tools, MCP, multi-provider, tracing — where they now basically tie. That's the wrong axis. What actually separates them is who holds control when a run goes wrong.
Here's the fast version, then the reasoning.
The one-line answer#
- On AutoGen or Semantic Kernel already, or a .NET shop? → Microsoft Agent Framework. It's the merger of both, and both predecessors are now in maintenance mode.
- Can't tolerate a half-finished run? → LangGraph. It's durable by construction; a run survives a server restart.
- Want an agent loop running this afternoon? → OpenAI Agents SDK. Agents, handoffs, guardrails, minimal ceremony.
Everything below is why those three sentences are the whole decision.
Microsoft Agent Framework: the consolidation is the news#
The most consequential agent-framework event of 2026 wasn't a new tool — it was two old ones ending. On April 3, 2026, Microsoft shipped Agent Framework 1.0 (GA), folding AutoGen and Semantic Kernel into a single SDK. Semantic Kernel became the foundation layer — session state, type safety, middleware, telemetry — and AutoGen-style multi-agent orchestration became a graph workflow on top. It ships .NET and Python in parallel under Microsoft.Agents.AI, with the same concepts and API shape on both.
At 1.0 it's genuinely batteries-included: native MCP for tools and native A2A for cross-framework agent-to-agent collaboration (neither bolt-on), six model providers (Azure OpenAI, OpenAI, Anthropic, Bedrock, Gemini, Ollama) with one-line swaps, and DevUI, a browser debugger you launch with agent-framework devui that surfaces traces, message flows, and tool calls live.
The part that forces a decision: both AutoGen and Semantic Kernel went into maintenance mode — bug and security fixes only, no new features. If you're on either, this isn't a framework to evaluate against the others. It's your migration target.
The Microsoft move wasn't shipping a framework. It was retiring two, and pointing everyone on them at one door.
LangGraph: you pay in wiring, you get durability#
LangGraph (1.0 in October 2025, 1.2 on May 12, 2026) makes a different bet. You model the agent as an explicit state graph — nodes, edges, a typed state object — and in exchange the runtime checkpoints that state so a run survives a server restart. That is the entire pitch, and it's a good one for anything where a 20-step run dying at step 12 means lost work or a double-charged customer.
1.2 hardened exactly that story: per-node timeouts (a hard run_timeout wall-clock cap, an idle_timeout that resets on progress, or both), delta-only checkpoints via DeltaChannel so a long message thread doesn't re-serialize on every step, and a RunControl primitive for graceful shutdown that leaves a resumable checkpoint behind. It also leads the category in mindshare — roughly 27,100 monthly searches, the top of the pack per Langfuse's framework comparison.
The cost is real: you author the control flow. There's more up-front structure than a handoff loop — the same trade-off that shows up when you weigh LlamaIndex Workflows against LangGraph, or LangGraph against CrewAI and AutoGen: explicitness buys you guarantees and costs you boilerplate. That structure is the price of the durability guarantee, and if you don't need the guarantee, you're paying for nothing.
OpenAI Agents SDK: the lightweight loop#
The OpenAI Agents SDK went GA in March 2025, replacing the experimental Swarm, and its model is deliberately small: agents, handoffs between them, and guardrails around them. By v0.13 it grew the things that make it viable beyond a demo — an any-LLM adapter (so it's no longer OpenAI-only), session persistence, MCP resource support, opt-in retry policies, and a realtime model default bump.
It is the fastest of the three to a working loop, and the least opinionated about structure. What it doesn't give you is durable-by-construction state — session persistence is not the same as "the run resumes after the process dies." For a lot of agents, that's fine. For a payment or provisioning workflow, it's the gap that sends you to LangGraph.
How to actually choose#
Ignore the feature checklist — all three now do tools, MCP, multiple providers, and tracing. Decide on control model and failure semantics:
- Who owns control flow? An explicit graph you author (LangGraph), an orchestration layer over enterprise primitives (Microsoft), or a minimal handoff loop (OpenAI).
- What happens when the process dies mid-run? Durable resume (LangGraph), session state you rehydrate (Microsoft, OpenAI), or you re-run (OpenAI unless you build it).
- What runtime are you on? .NET makes the decision for you — Microsoft is the only first-class answer.
Pick on those three and the tie on features stops mattering. That's the point: in 2026, the frameworks converged on what they do. They still disagree on who's holding the controls — and that's the only question worth deciding on.
