Models · VLA (vision-language-action)
smolvla/so101
checking availability…
A specific checkpoint, edge-
Price
- per call
- $0.005 · 50 tokens
- per action
- $0.0001
- billed
- every returned action, whether or not your robot plays it
What you send
observation.state[6]- shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper · normalized: arm -100..100, gripper 0..100
observation.images.front[480, 640, 3]- front camera, RGB uint8 (JPEG on the wire)
observation.images.wrist[480, 640, 3]- wrist camera, RGB uint8 (JPEG on the wire)
tasktext- passed to the policy
What comes back
50 actions × 6 joints, to be played at 30 Hz — 1.67 s of motion per call.
semantics label depends on where you read it — the model catalog still answers so101-degrees-gripper-percent-v1, a lease and the wire answer the corrected label — and the data is normalized either way, so never branch on it (units, explained). LeRobot’s so101_follower defaults to degrees: run it with --robot.use_degrees=false. What the arm does if the connection drops.Measured
- policy
- 367–417 ms
- on the runner
- 382–446 ms
- client round trip
- 552–1141 ms
From a recorded probe on 2026-10-25 06:00Z. The round trip includes that client’s network; yours will differ. What each number measures.
Try it
One billed call with synthetic inputs ($0.005). No robot moves.
pip install agi-diy
agi login
agi run smolvla/so101 --probe -n 1Needs Python 3.12 — LeRobot is installed on first use, requires 3.12 or later and does not run on 3.14 yet.
Or run a test call from the dashboard, or drive the simulated SO-101.
Licences and data
| Checkpoint | edge-71cf4a9 · 1.2 GB | apache-2.0 |
|---|---|---|
| Base model | lerobot/ | apache-2.0 |
| Training data | LightwheelAI/ | apache-2.0 |
Licences as declared on the Hub at the pinned revision. Policies, explained.