README.md

---
base_model:
- Qwen/Qwen3-8B
datasets:
- OpenThoughts-Agent-v1-SFT
- OpenThoughts-Agent-v1-RL
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- agents
- terminal
- code
- software-engineering
model-index:
- name: OpenThinker-Agent-v1
  results: []
---

<p align="center">
    <img src="https://huggingface.co/datasets/open-thoughts/OpenThoughts1-Agent-SFT/resolve/main/ota-logo.png" width="50%">
</p>

<p align="center">
<a href="https://huggingface.co/papers/2606.24855" style="margin-right: 24px;">Paper</a> |
<a href="https://www.openthoughts.ai/blog/agent" style="margin-right: 24px; margin-left: 24px;">Project</a> |
<a href="https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-SFT" style="margin-right: 24px; margin-left: 24px;">SFT dataset</a> |
<a href="https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-RL" style="margin-right: 24px; margin-left: 24px;">RL dataset</a> |
<a href="https://huggingface.co/open-thoughts/OpenThinker-Agent-v1-SFT" style="margin-right: 24px; margin-left: 24px;">SFT model</a> |
<a href="https://huggingface.co/open-thoughts/OpenThinker-Agent-v1" style="margin-left: 24px;">RL model</a>
</p>


# OpenThinker-Agent-v1

**OpenThoughts-Agent** is an open-source effort to curate the best datasets for training agents. Our first release includes [datasets](https://huggingface.co/collections/open-thoughts/openthinker-agent), [models](https://huggingface.co/collections/open-thoughts/openthinker-agent) and our [research codebase](https://github.com/open-thoughts/OpenThoughts-Agent). For more details, please see our paper: [OpenThoughts-Agent: Data Recipes for Agentic Models](https://huggingface.co/papers/2606.24855).

[OpenThinker-Agent-v1](https://huggingface.co/open-thoughts/OpenThinker-Agent-v1) is a model trained for agentic tasks such as **Terminal-Bench 2.0** and **SWE-Bench**.

The [OpenThinker-Agent-v1](https://huggingface.co/open-thoughts/OpenThinker-Agent-v1) model is post-trained from [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B).
It is SFT-ed on the [OpenThoughts-Agent-v1-SFT](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-SFT) dataset, then RL-ed on the [OpenThoughts-Agent-v1-RL](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-RL) dataset. 

This model is the final model after both SFT and RL. For the model after the SFT stage only, see [OpenThinker-Agent-v1-SFT](https://huggingface.co/open-thoughts/OpenThinker-Agent-v1-SFT).

- **Paper:** https://huggingface.co/papers/2606.24855
- **Homepage:** https://www.openthoughts.ai/blog/agent
- **Repository:** https://github.com/open-thoughts/OpenThoughts-Agent


# OpenThinker-Agent-v1 Model Performance

Our [OpenThinker-Agent-v1](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-RL) model is the state-of-the-art model at its scale on agent benchmarks.

| Model                                                                                           | Harness | Terminal-Bench 2.0 | SWE-Bench Verified | OpenThoughts-TB-Dev |
| ----------------------------------------------------------------------------------------------- | ------- | ------------------ | --------- | ------------------- |
| [Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)                                                | Terminus-2 | 0.0             | 0.7       | 5.7                 |
| **[OpenThinker-Agent-v1](https://huggingface.co/open-thoughts/OpenThinker-Agent-v1)**           | Terminus-2 | 4.9             | 15.7      | 17.3                |
| [Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B)                                              | Terminus-2 | 1.9             | 5.7       | 10.2                |
| [Qwen/Qwen3-Coder-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct)   | OpenHands  | 10.1           | 49.2      |  24.5                |


# Data

We built [OpenThinker-Agent-v1](https://huggingface.co/open-thoughts/OpenThinker-Agent-v1) in two stages: **supervised fine-tuning**, followed by **reinforcement learning**. 
Each stage required its own data pipeline – RL tasks (instructions, environments, and verifiers) and SFT traces from strong teacher agents completing tasks.

[OpenThoughts-Agent-v1-SFT](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-SFT) is an SFT trace dataset containing approximately **15,200 traces** drawn from two different data sources we curate:
- **nl2bash**: Simple synthetically generated tasks where the agent has to format shell commands effectively
- **InferredBugs**: A set of bugs in C# and Java collected by Microsoft that we turned into tasks

[OpenThoughts-Agent-v1-RL](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-RL) is an RL dataset containing ~720 tasks drawn from the **nl2bash verified** dataset.

To stabilize training, we built a three-stage filtration pipeline that prunes tasks before they ever hit the learner:

1. Bad verifiers filter: drop tasks with flaky or excessively slow verifiers.
2. Environment stability: remove tasks whose containers take too long to build or tear down.
Optional difficulty filter: discard tasks that even a strong model (GPT-5 Codex) cannot solve in a single pass.


# Links
- 📄 [OpenThoughts-Agent Paper](https://huggingface.co/papers/2606.24855)
- 🌐 [OpenThoughts-Agent project page](https://www.openthoughts.ai/blog/agent)
- 💻 [OpenThoughts-Agent GitHub repository](https://github.com/open-thoughts/OpenThoughts-Agent)
- 🧠 [OpenThoughts-Agent-v1-SFT dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-SFT)
- 🧠 [OpenThoughts-Agent-v1-RL dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-v1-RL)
- 🧠 [OpenThoughts-TB-dev dataset](https://huggingface.co/datasets/open-thoughts/OpenThoughts-TB-dev)
- 🤖 [OpenThinker-Agent-v1 model](https://huggingface.co/open-thoughts/OpenThinker-Agent-v1)
- 🤖 [OpenThinker-Agent-v1-SFT model](https://huggingface.co/open-thoughts/OpenThinker-Agent-v1-SFT)


# Citation
```
@misc{openthoughts-agent,
  author = {Team, OpenThoughts-Agent},
  month = Dec,
  title = {{OpenThoughts-Agent}},
  howpublished = {https://www.open-thoughts.ai/blog/agent},
  year = {2025}
}
```