OpenThinkerAgent-32B-SFT-1K

<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://www.openthoughts.ai/blog/agent" style="margin-right: 24px;">Project</a> | <a href="https://github.com/open-thoughts/OpenThoughts-Agent" style="margin-right: 24px; margin-left: 24px;">Code</a> | <a href="https://huggingface.co/collections/open-thoughts/openthinker-agent" style="margin-left: 24px;">Collection</a> </p>

OpenThinkerAgent-32B-SFT-1K

OpenThoughts-Agent is an open-source effort to curate the best datasets for training agents. Our release includes datasets, models and our research codebase.

OpenThinkerAgent-32B-SFT-1K is post-trained from Qwen/Qwen3-32B with full-parameter SFT on the 1,000-example OpenThoughts-Agent-SFT-1K dataset (Top-4 task sources, GLM-4.7-AWQ teacher in the terminus-2 harness, ≥5-turn trace filter).

• Homepage: https://www.openthoughts.ai/blog/agent
• Repository: https://github.com/open-thoughts/OpenThoughts-Agent

Performance

Evaluated in the terminus-2 harness (pass@1, mean over 3 stochastic re-runs):

Data

The model is trained on OpenThoughts-Agent-SFT-1K: (task, agent-trajectory) pairs from the Top-4 task sources (SWE-Smith, StackExchange-SuperUser, StackExchange-Tezos with synthetic augmentation, IssueTasks). Trajectories are generated by GLM-4.7-AWQ in the terminus-2 harness and filtered to traces with at least 5 model turns.

Training hyperparameters

• learning_rate: 4e-05
• lr_scheduler_type: cosine, warmup_ratio 0.1
• global_batch_size: 96
• num_epochs: 7
• cutoff_len: 32768
• precision: bf16, DeepSpeed ZeRO-3

Links

• 🌐 OpenThoughts-Agent project page
• 💻 OpenThoughts-Agent GitHub repository
• 📚 OpenThinker-Agent collection
• 🧠 Training dataset: OpenThoughts-Agent-SFT-1K

Citation

@misc{openthoughts-agent,
  author = {Team, OpenThoughts-Agent},
  title = {{OpenThoughts-Agent: Data Recipes for Agentic Models}},
  howpublished = {https://www.openthoughts.ai/blog/agent},
  year = {2026}
}