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Agnov3.1.10Tested (smoke test)

Agno: what’s new in v3.1.10 and our verdict

Open-source agent framework that now sells a self-driving agent platform you run in your own cloud.

Official site

Release Ruler for Agno: marked at its Tested release date on the timeline of every AI model we track.

At a glance

Evidence
Tested (smoke test)
Released
Oct 23, 2026
Last verified
Oct 25, 2026
Pricing
Partly verified
Best for
agent building

Evidence and ranking

Evidence behind this verdict

  1. Sources read2 cited sources, latest fetched Oct 25, 2026. (done)
  2. Facts re-checkedLast verified Oct 25, 2026. (done)
  3. Run by usSmoke test on Oct 25, 2026 (scope below). (done)

Passed Test log result: Passed. Read the log

Where we rank it (editorial)

Listed here but not yet ranked. Ranks are editorial picks, not benchmark scores.

Pricing: No pricing page read. (checked 2026-10-25)

Our verdict

Open-source agent framework that now sells a self-driving agent platform you run in your own cloud.

Good for

  • Teams that want to run agents in their own cloud

Skip if

  • You need a no-code builder

Tested. Tested 2026-10-25 (America/Chicago). Agno 3.1.10 passed our one-tool task on a local 3B model: 3 of 3 trials; cold uv install 1.8 s. Test environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key. Agent tools were pointed at a local open-weight model (Qwen2.5-3B-Instruct (Q4_K_M) through Ollama 0.40.11), so we tested the tool, not any vendor's hosted models. Not tested: Any vendor-hosted model: everything ran on a local 3B model, so tool-call reliability with frontier models is not measured here; Multi-agent flows, memory, long conversations, streaming, tracing and cloud deployment; Anything beyond one tool and one question; three trials is a smoke test, not a benchmark. These are smoke tests, not a benchmark. Full log: /tests/agno.

Full test log with exact commands, versions and raw output: Agno 3.1.10: our test log.

Evidence
Tested (smoke test, 2026-10-25, local 3B model (Qwen2.5-3B)). A smoke test is not a benchmark.
What we ran
Agno 3.1.10 passed our one-tool task on a local 3B model: 3 of 3 trials; cold uv install 1.8 s.
Model used
Qwen2.5-3B-Instruct (Q4_K_M) through Ollama 0.40.11
Environment
Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key
Not tested
Any vendor-hosted model: everything ran on a local 3B model, so tool-call reliability with frontier models is not measured here; Multi-agent flows, memory, long conversations, streaming, tracing and cloud deployment; Anything beyond one tool and one question; three trials is a smoke test, not a benchmark.
Date
(America/Chicago)

Best for

Key facts

Agno's site describes an agent platform that runs in your cloud so you can build, deploy and improve customer-facing and internal agents. The repository is Apache-2.0; v3.1.10 was tagged Oct 23, 2026.

  • License: Apache-2.0 (per GitHub)
  • Platforms: Python; runs in your cloud
  • Pricing model: Open source + platform
  • Free tier: Open-source framework free
  • Paid plans: Platform pricing not read
  • GitHub: agno-agi/agno: 42,890 stars on 2026-10-25, last push 2026-10-25
  • Latest release we saw: v3.1.10, 2026-10-23
  • How to start: Install agno from pip and follow the docs; the platform needs sign-up via agno.com.
  • v3.1.10 (2026-10-23): the newest release listed on the official page or repository when we read it on 2026-10-25.

How to set it up: Get started with Agno

These steps come from the vendor's own pages as read on 2026-10-25. We ran Agno on 2026-10-25; the test log lists what was and was not covered.

  1. Get access

    Install agno from pip and follow the docs; the platform needs sign-up via agno.com.

  2. Check the limits and costs first

    Open-source framework free. Paid: Platform pricing not read. No pricing page read.

Pros and cons

Pros

  • Apache-2.0
  • Frequent releases

Cons

  • Platform pricing not read
  • Our test was one small task on a local 3B model; it does not show behaviour with hosted models or larger jobs

Alternatives and comparisons

  • CrewAI: Python framework for orchestrating role-playing, autonomous AI agents that work as a crew.
  • LangGraph: Low-level framework for building long-running, stateful agents as graphs.
  • Pydantic AI: Python agent framework built on Pydantic types, covering agents, realtime voice, image generation and embeddings.
  • Langflow: MIT-licensed visual builder for AI agents and MCP servers with a very large GitHub following.

FAQ

What is Agno?

Agno's site describes an agent platform that runs in your cloud so you can build, deploy and improve customer-facing and internal agents. The repository is Apache-2.0; v3.1.10 was tagged Oct 23, 2026.

Is Agno free?

Open-source framework free. Paid: Platform pricing not read. No pricing page read. Checked 2026-10-25; prices change, so confirm on the vendor's page.

What license is Agno under?

Its license: Apache-2.0 (per GitHub). Read from the project's own pages on 2026-10-25.

What we have not verified

  • Platform pricing

Sources

Last verified · Agentic Weekly

  • Langflow: MIT-licensed visual builder for AI agents and MCP servers with a very large GitHub following.
  • Botpress: Customer-support AI agent platform with a free plan and conversation-based paid plans.
  • Gumloop: Agent builder for teams; plans start at $37 per month with 20k included credits.

How to cite this page

Agentic Weekly, "Agno v3.1.10: what's new, verdict & setup", last updated 2026-10-25, https://theagenticweekly.com/tools/agno

Keep the Reported or Tested label when you quote a verdict. Plain-text version: https://theagenticweekly.com/tools/agno.md. More for AI assistants: /ai, /tools.json, /llms.txt.