DM05-ARX5 (RoboChallenge)

OpenDM-format BF16 checkpoint for ARX5 on RoboChallenge Table 30 v2. Use with OpenDM third_party/robochallenge_inference (configs/generalist/arx5.yaml). See the DM05 RoboChallenge Table 30 v2 Inference Guide.

Weights: BF16 model.safetensors.

Model Card

Field	Value
Config	`generalist/arx5`
Env vars	`ARX5_CHECKPOINT` / `ARX5_NORM_STATS`
OpenDM `robot_type`	`ARX5`
Control	EEF relative (`single_arm_target=eef`)
Cameras	Head / Left wrist / Right wrist
Platform cams	`cam_global` → image_0, `cam_side` → image_1, `cam_arm` → image_2
Native state / action stats	7 / 7 (action-only quantile `norm_stats.json`)
Defaults	`action_horizon=50`, `action_playback_target_steps=25`, `history_mode=logical_step`, `is_history=true`

Table30 Tasks

arrange_flowers, hang_the_cup, pick_out_the_green_blocks, press_the_button, turn_on_the_light_switch, water_the_flowers, wipe_the_table

Per-task horizon overrides: third_party/robochallenge_inference/configs/generalist/arx5.yaml → task_overrides.

Use with OpenDM RoboChallenge Inference

The RoboChallenge client now lives in OpenDM at third_party/robochallenge_inference (configs/generalist/arx5.yaml). See the DM05 RoboChallenge Table 30 v2 Inference Guide.

# From the OpenDM repository root.
export OPENDM_ROOT=/path/to/opendm
pip install -e ".[fast-infer]"

cd third_party/robochallenge_inference
export ARX5_CHECKPOINT=/path/to/DM05-ARX5
export ARX5_NORM_STATS=${ARX5_CHECKPOINT}/norm_stats.json
pip install -r requirements.txt

python execute.py --config-name generalist/arx5 \
  user_id=YOUR_USER_ID \
  submission_id=YOUR_SUBMISSION_ID

Override without env vars:

python execute.py --config-name generalist/arx5 \
  checkpoint=/path/to/DM05-ARX5 \
  norm_stats=/path/to/DM05-ARX5/norm_stats.json \
  user_id=YOUR_USER_ID \
  submission_id=YOUR_SUBMISSION_ID

If ARX5_NORM_STATS is unset, the client falls back to ${ARX5_CHECKPOINT}/norm_stats.json.

Runtime Profile

From third_party/robochallenge_inference/configs/default.yaml → robot_profiles.arx5:

action_type=leftpos, action_mode=relative, single_arm_target=eef
history_mode=logical_step, history_max_frames=5
speed=0.5, add_state=true
attn: llm/action sdpa, vision flash_attention_2

Files

.
├── config.json
├── model.safetensors
├── norm_stats.json
├── tokenizer.json
├── tokenizer_config.json
├── processor_config.json
├── chat_template.jinja
├── generation_config.json
└── README.md

Citation

@misc{dm05,
    title  = {{DM0.5}: An Open-World Foundation Model for General-Purpose Embodied Intelligence},
    author = {{Dexmal Team}},
    month  = {July},
    year   = {2026},
    url    = {https://www.dexmal.com/blog/dm0.5/index_en.html}
}