Performance Benchmarks: Latency in Agentic Frameworks

All answers to this question.

Our internal benchmarks show that the OpenAI Agents SDK is roughly 15-20% faster in "time-to-first-token" compared to a similar LangChain setup. This isn't because the model is faster—it’s the same GPT-5.4—but because the SDK has a much thinner processing layer. LangChain often runs multiple pre-processing steps, prompt formatting, and "output parsing" logic that adds a few hundred milliseconds to every turn. In a multi-agent system where three agents might talk to each other before replying to the user, those milliseconds add up to seconds of lag. If you are building a voice-based agent or a high-speed chat interface, the SDK is definitely the way to go for the performance gains alone.

   Answered 2025-09-15 by Deborah Lewis

Does the SDK support asynchronous execution for all agents, or are handoffs purely sequential?

   Answered 2025-10-01 by Andrew Ford

• Andrew, the SDK is built on top of Python’s asyncio from the ground up. You can easily run multiple agents in parallel or have an orchestrator agent wait for results from several sub-agents simultaneously. This is a huge benefit for speed. In LangChain, doing this often required complex "AsyncCallbackHandlers" that were a nightmare to implement correctly, but here it’s just standard async Python.

     Commented 2025-10-10 by Gerald Fox

Performance is the main reason I switched. The SDK feels like writing a modern web app, whereas LangChain feels like writing a legacy Java enterprise app.

   Answered 2025-11-15 by Pamela King

• Haha, I love that comparison, Pamela! Julia, if speed is your bottleneck, the move to the SDK will give your users a much more "instant" experience.

     Commented 2025-11-22 by Julia Gardner