tmax-8b

Image: image

💻 Code · 🤗 Models & Data · 📜 Paper · 📓 Blog

Note. For full information, go check out the Tmax paper here.

TMax 8B#

TMax 8B is a model trained using DPPO on top of Qwen 3 8B for use as a terminal-agent.

This model is part of a collection of terminal agents in various sizes.

The main branch is the step 300 checkpoint as that performed best on tblite.

Evaluation Results#

For details on evaluation methodology please check our paper. In general, we used a podman (docker) backend with default timeouts and custom harness similar to mini-swe-agent.

Model Details#

Model Description#

• Developed by: Ai2
• Language(s) (NLP): English
• License: Apache 2.0
• Finetuned from model [optional]: Qwen 3 8B
• Dataset: TMax-15k

Use#

To use this model, we recommend serving with vllm (or your inference framework of choice) with:

uvx vllm==0.19.1 serve allenai/tmax-8b \
  --served-model-name tmax-8b \
  --enable-auto-tool-choice \
  --tool-call-parser qwen3_xml \
  --port 8008 \
  --max-model-len 40960 \
  --tensor-parallel-size 8 \
  --language_model_only

Make sure to set language_model_only as we removed the vision head during training.

For more details on evaluation, please see our codebase.

Hyperparameters#

This model was trained using DPPO with the following hyperparameters:

• base model: allenai/tmax-sft-8b
• Dataset: tmax 15K
• Max prompt tokens: 2048
• Max per-turn tokens: 16384
• Max overall tokens: 32768
• Pack length: 34816
• Per-device train batch size: 1
• Unique prompts per rollout: 32
• Samples per prompt rollout: 8
• Async steps: 4
• Max steps: 64
• Learning rate: 1e-6
• LR scheduler: constant
• Total training steps: 500 steps
• Sampling Temperature: 1.0
• KL Beta: 0.0
• Loss fn: DPPO
• Divergence: binary TV
• TV threshold: 0.1
• Advantage normalization: centered (no division by stdev)
• FP32 LM head: true

For more details on training, please see our codebase.

License#

This model is licensed under Apache 2.0. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines.

Citation#

If you use our model or data, please cite our paper:

@misc{ivison2026tmaxsimplerecipeterminal,
      title={Tmax: A simple recipe for terminal agents}, 
      author={Hamish Ivison and Junjie Oscar Yin and Rulin Shao and Teng Xiao and Nathan Lambert and Hannaneh Hajishirzi},
      year={2026},
      eprint={2606.23321},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2606.23321}, 
}