Selector guide · from the official model card
Which SONIC model do you need? Three checkpoints, one decision
GEAR-SONIC ships three whole-body controller checkpoints for the Unitree G1. They differ in reference horizon and deployment intent — pick by how you will use the controller, not by version number. Everything below is transcribed from the official model card.
Available models
| Model | SMPL reference input | Intended use |
|---|---|---|
| Default SONIC (original release) | 10 future frames at 20 ms spacing, approximately 200 ms of reference lookahead | Default general-purpose SONIC controller for motion tracking, planning, teleoperation, and compatibility with existing deployments. G1 and teleoperation future-reference observations use step5. |
| Low-latency teleoperation | 4 future frames at 20 ms spacing, approximately 80 ms of reference lookahead | Intended for more responsive whole-body teleoperation and VLA execution. G1 and teleoperation future-reference observations use step1. Use its encoder, decoder, and observation config together. HF files → |
| SONIC v1.1 | 10 future frames at 20 ms spacing, approximately 200 ms of reference lookahead | Uses robot-heading-normalized target orientation and was trained with wrist-pose augmentation. Intended for heading-stable whole-body teleoperation and SONIC-backed VLA policies that use this controller. G1 and teleoperation future-reference observations use step5; this is not the low-latency model. HF files → |
Pick by use case
Default SONIC
Motion tracking, planning, teleoperation, and compatibility with existing deployments. The safe default when you are not sure — it is the original general-purpose release.
Low-latency teleoperation
Most responsive whole-body teleoperation and VLA execution. 4-frame lookahead (~80 ms). Use its encoder, decoder, and observation config together — do not mix with the default files.
SONIC v1.1
Heading-stable whole-body teleoperation and SONIC-backed VLA policies. Robot-heading-normalized target orientation, trained with wrist-pose augmentation. Not the low-latency model.
Released files
| Model | Deployment files | PyTorch + config |
|---|---|---|
| Default SONIC | model_encoder.onnx, model_decoder.onnx, observation_config.yaml | sonic_release/last.pt, sonic_release/config.yaml |
| Low-latency teleoperation | low_latency/model_encoder.onnx, low_latency/model_decoder.onnx, low_latency/observation_config.yaml | low_latency/last.pt, low_latency/config.yaml, low_latency/model_config.yaml |
| SONIC v1.1 | sonic_v1_1/model_encoder.onnx, sonic_v1_1/model_decoder.onnx, sonic_v1_1/observation_config.yaml | sonic_v1_1/last.pt, sonic_v1_1/config.yaml, sonic_v1_1/model_config.yaml |
Deployment uses C++ and TensorRT; the PyTorch checkpoints support Isaac Lab evaluation and continued training. Model weights are covered by the NVIDIA Open Model License.