# Choosing an Open-Source Annotation Tool in 2026

Source: https://www.potatoannotator.com/blog/choosing-an-annotation-tool-2026

There is no single best annotation tool, and any article that tells you otherwise is selling something. The right choice comes down to what you're annotating, whether you need to evaluate LLMs and agents, your budget, and how much setup you can stomach. Here is how to narrow it down.

## The questions that actually decide it

**What are you annotating?** For text-only NER or classification, simple tools like Doccano or brat do the job with little ceremony. For a mix of text, images, audio, and video, you need something broader, which is where Potato and Label Studio come in.

**Do you need to evaluate agents or LLMs?** This is the question most tool comparisons skip, and it's where the field splits. Evaluating an agent means reading its trace, judging steps and tool calls, and sometimes watching it run live. Most general annotation tools weren't built for that. Potato reads agent traces in many formats and has dedicated tools for [trajectory evaluation](/docs/guides/agent-trajectory-annotation), [process reward labeling](/docs/guides/process-reward-models), and [web](/docs/guides/web-agent-evaluation) and [coding agent](/docs/guides/coding-agent-evaluation) review.

**What's your budget?** Potato, Label Studio's core, Doccano, brat, and Argilla are free and open-source. Prodigy and some Label Studio tiers are paid.

**How much setup can you tolerate?** Potato is configured with a YAML file and needs no code. Prodigy is code-first. The others sit in between.

**What ecosystem are you in?** Prodigy pairs tightly with spaCy. Argilla lives in the Hugging Face stack. Potato exports to CoNLL, spaCy, Hugging Face, and COCO/YOLO, so it slots into most pipelines.

## Where Potato fits

Potato came out of academic NLP and was built for the whole research workflow: many task types, agreement metrics and quality control in the box, crowdsourcing integrations, and a deep set of agent-evaluation tools added more recently. If your work spans several modalities or includes evaluating models and agents, it's worth a look.

If you mainly need one text task with a hosted commercial product, or you live entirely inside spaCy or Hugging Face, one of the others may suit you better. Pick the tool that fits the work, not the loudest pitch.

## Read more

The longer, side-by-side version is in the [Open-Source Annotation Tools Compared](/docs/guides/annotation-tools-compared) guide, and the case for Potato specifically is on [Why Potato](/why-potato). For a feature-level comparison from the source, see the [comparison documentation](https://github.com/davidjurgens/potato/blob/master/docs/comparison.md).