Comparisons / Agno vs OpenAI Agents SDK
Agno vs OpenAI Agents SDK: Which Agent Framework to Use?
Agno (formerly Phidata) is a lightweight Python framework for building agents. OpenAI's Agents SDK (evolved from Swarm) provides Agent, Runner, handoffs, and guardrails. Here is how they compare — paradigm, ecosystem, and the use cases each one is actually built for.
By the numbers
Agno
39.2k
5.2k
Python
Apache-2.0
2022-05-04
Agno (formerly Phidata)
OpenAI Agents SDK
20.6k
3.4k
Python
MIT
2025-03-11
OpenAI
GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.
| Concept | Agno | OpenAI Agents SDK |
|---|---|---|
| Agent | `Agent(model=OpenAIChat(), instructions=[...])` class with `run()` method | `Agent(name, instructions, model, tools)` |
| Tools | Function tools via `@tool` decorator or built-in toolkits (web search, SQL, etc.) | Python functions with type hints, auto-converted to schemas |
| Agent Loop | `Agent.run()` handles tool dispatch internally, configurable via `show_tool_calls` | `Runner.run()` handles the loop internally |
| Memory / Knowledge | Knowledge bases (PDF, URL, vector DB) injected via `knowledge` param + built-in memory | — |
| Multi-Agent (Teams) | `Team` class with `agents` list, `mode` (sequential, parallel, coordinate), and shared memory | — |
| Storage | `SqlAgentStorage`, `PostgresAgentStorage` for persisting sessions and state | — |
| Handoffs | — | `Handoff` between `Agent` objects for multi-agent routing |
| Guardrails | — | `InputGuardrail` and `OutputGuardrail` with tripwire pattern |
| Context | — | Typed context object passed through the agent lifecycle |
Agno vs OpenAI Agents SDK, head to head
Agno Agno (formerly Phidata) is a lightweight Python framework for building agents.
OpenAI Agents SDK OpenAI's Agents SDK (evolved from Swarm) provides Agent, Runner, handoffs, and guardrails.
Both wrap the same underlying agent pattern — an LLM call, a tool dispatch, a loop — in different abstractions. The choice between them is mostly about which mental model and ecosystem fits the team you have, not which one is technically more capable.
Pick Agno if
Pick Agno if agno adds value when you want a batteries-included agent with minimal boilerplate — especially for multi-modal agents or team orchestration. But each of its abstractions maps to a small piece of plain Python. If your agent is straightforward, writing it directly gives you full control with zero framework overhead. Agno is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; OpenAI Agents SDK would force you to translate.
Pick OpenAI Agents SDK if
Pick OpenAI Agents SDK if the Agents SDK is the thinnest framework on this list — it barely abstracts beyond what you'd write yourself. Use it when you want OpenAI's conventions and auto-schema generation. Skip it when you want full control or use non-OpenAI models. OpenAI Agents SDK is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Agno would force you to translate.
What both add
Both Agno and OpenAI Agents SDK pull in a class hierarchy and a dependency tree to wrap what is, at the core, an HTTP POST in a while loop. If your use case is straightforward — one provider, a handful of tools, a single agent — the framework cost may exceed the framework benefit. The lesson below shows the same pattern in ~60 lines without either dependency.
Or build your own in 60 lines
Both Agno and OpenAI Agents SDK implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.
No framework. No dependencies. No opinions. Just the code.
Build it from scratch →