LeRobot releases RynnValue-4B reward model for predicting robotic task completion time

lerobot/RynnValue-4B

Summary

LeRobot has released RynnValue-4B, a language-conditioned robotic value model built on Qwen3-VL that predicts the remaining time in seconds until a task is completed given a trajectory video and task description. The model is inference-only within the LeRobot ecosystem and cannot be trained using lerobot-train. It is available under an Apache-2.0 license.

Editorial context

The model predicts remaining task completion time in seconds from video trajectories and text descriptions, licensed under Apache-2.0.

Source: LeRobot — Model repository updates · Read original article ↗

Article text · Original source · English

On this page

Reward Model Card for rynnvalue

RynnValue is a language-conditioned robotic value model built on Qwen3-VL. Given a trajectory video and a task description, it predicts the remaining time, in seconds, until the task is completed.

This reward model is inference-only in LeRobot: it can't be trained with lerobot-train.

See the full documentation at LeRobot Docs.

How to Get Started with the Reward Model

Load the reward model in Python

from lerobot.configs.rewards import RewardModelConfig
from lerobot.rewards import make_reward_model

config = RewardModelConfig.from_pretrained("lerobot/RynnValue-4B")
reward_model = make_reward_model(config)

# `batch` is the output of this model's preprocessor.

remaining_time_s = reward_model.predict_remaining_time(batch).remaining_time_s

Model Details

License: apache-2.0

What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

Dataset details reported by the source

License: apache-2.0 Open source S3

code: not_reported
paper: not_reported
weights: not_reported
dataset: not_reported

What remains unknown

Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

model in Python from lerobot.configs.rewards import RewardModelConfig from lerobot.rewards import make_reward_model config = RewardModelConfig.from_pretrained( "lerobot/RynnValue-4B" ) reward_model = make_reward_model(config) # `batch` is the output of this model's preprocessor. remaining_time_s = reward_model.predict_remaining_time(batch).remaining_time_s Model Details License: apache-2.0
Open source S3

Reward Model Card for rynnvalue RynnValue is a language-conditioned robotic value model built on Qwen3-VL. Given a trajectory video and a task description, it predicts the remaining time, in seconds, until the task is completed. This reward model is inference-only in LeRobot : it can't be trained with lerobot-train . See the full documentation at LeRobot Docs . How to Get Started with the Reward Model Load the reward
Open source S2

lerobot/RynnValue-4B
Open source S1

Implications for data suppliers

RoboSignal interpretation and collection questions, not statements of buyer demand.

Confirm the required data type and collection setting with the buyer; this source does not establish a complete collection specification.
Check the exact dataset version, license, modalities and task coverage against the intended use.
Validate demand and acceptance criteria with a buyer before scaling. Publication, popularity and a research result do not establish a purchase commitment.