OpenThinkerAgent-32B-SFT-10K API & Inference Endpoint

OpenThinkerAgent-32B-SFT-10K

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-10K is post-trained from Qwen/Qwen3-32B with full-parameter SFT on the 10,000-example OpenThoughts-Agent-SFT-10K 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):

Table with columns: Model, Harness, SWE-Bench-Verified-100, OpenThoughts-TBLite, Terminal-Bench 2.0
Model	Harness	SWE-Bench-Verified-100	OpenThoughts-TBLite	Terminal-Bench 2.0
Qwen/Qwen3-32B	Terminus-2	26.7	13.7	7.5
OpenThinkerAgent-32B-SFT-10K	Terminus-2	35.0	33.2	16.9

Data

The model is trained on OpenThoughts-Agent-SFT-10K: (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

Citation

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