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deepsetv3.4.1Tested (smoke test)

Haystack: what’s new in v3.4.1 and our verdict

Apache-2.0 Python framework for building search, RAG and agent pipelines, maintained by deepset.

Official site

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

At a glance

Evidence
Tested (smoke test)
Released
Oct 21, 2026
Last verified
Oct 25, 2026
Pricing
Official page, dated
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: Open-source library; costs come from the model APIs you call. (checked 2026-10-25)

Our verdict

Apache-2.0 Python framework for building search, RAG and agent pipelines, maintained by deepset.

Good for

  • Production RAG pipelines
  • Teams that like explicit pipeline components

Skip if

  • You want a visual builder

Tested. Tested 2026-10-25 (America/Chicago). Haystack 3.4.1 passed our one-tool task on a local 3B model: 3 of 3 trials; cold uv install 2.3 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; Document stores, retrieval pipelines and evaluation. These are smoke tests, not a benchmark. Full log: /tests/haystack.

Full test log with exact commands, versions and raw output: Haystack 3.4.1: 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
Haystack 3.4.1 passed our one-tool task on a local 3B model: 3 of 3 trials; cold uv install 2.3 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; Document stores, retrieval pipelines and evaluation.
Date
(America/Chicago)

Best for

Key facts

Haystack's repository is Apache-2.0 licensed with v3.4.1 tagged Oct 21, 2026 and a push on Oct 24, 2026.

  • License: Apache-2.0 (per GitHub)
  • Platforms: Python
  • Pricing model: Free and open source
  • Free tier: Free to self-host
  • Paid plans: None listed for the library
  • GitHub: deepset-ai/haystack: 26,842 stars on 2026-10-25, last push 2026-10-24
  • Latest release we saw: v3.4.1, 2026-10-21
  • How to start: Install haystack-ai with pip and follow the quickstart in the docs.
  • v3.4.1 (2026-10-21): 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 Haystack

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

  1. Get access

    Install haystack-ai with pip and follow the quickstart in the docs.

  2. Check the limits and costs first

    Free to self-host. Open-source library; costs come from the model APIs you call.

Pros and cons

Pros

  • Apache-2.0
  • Active releases

Cons

  • Python only
  • 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

  • LlamaIndex: Open-source data framework for retrieval-augmented generation and document-centred agents, with a hosted document platform alongside.
  • LangChain: Open-source framework for building LLM applications and agents in Python and JavaScript, from the team behind LangGraph and LangSmith.
  • Dify: Open-source platform for building LLM apps and agent workflows with a visual canvas; licensed under a modified Apache 2.0 with extra conditions.
  • Langflow: MIT-licensed visual builder for AI agents and MCP servers with a very large GitHub following.

See all alternatives to Haystack

FAQ

What is Haystack?

Haystack's repository is Apache-2.0 licensed with v3.4.1 tagged Oct 21, 2026 and a push on Oct 24, 2026.

Is Haystack free?

Free to self-host. Open-source library; costs come from the model APIs you call. Checked 2026-10-25; prices change, so confirm on the vendor's page.

What license is Haystack under?

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

What we have not verified

  • Hosted 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, "Haystack v3.4.1: what's new, verdict & setup", last updated 2026-10-25, https://theagenticweekly.com/tools/haystack

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