CFG-1
The robot foundation model, built on real data.
CFG-1 is Config’s first-generation foundation model for bimanual manipulation — trained on in-house human and robot data, and adaptable to new tasks with hours of teleop.
2B
Parameters
10K+
Training hours · in-house
<50ms
Inference latency
3 min
Native memory
Approach
Human data, converted to robot data.
Most robotics foundation models scale by collecting more robot teleoperation data — expensive, slow, and operationally heavy. CFG-1 takes a different path.
01 · Source
Leveraging the scale and precision of human data.
Most of CFG-1's data comes from humans performing tasks — far faster and cheaper to scale than teleop — mixed with high-precision robot teleop.
02 · Conversion
Translate the data, don't reshape the model.
Our Conversion Engine maps human demonstrations into train-ready robot data at micrometer precision — the data quality of teleop, at a fraction of the cost.
03 · Scale
Built for industrial throughput.
Our Hanoi Data Studio runs 100+ operators producing ~20,000 hours of human data a month. With teleop collection in Seoul, Config has collected 200,000+ hours across 10,000+ tasks.
04 · Adaptation
Fine-tuned to your task in hours.
CFG-1 reaches 80%+ task success with just 1 hour of task-specific teleop data.
Architecture
Long-horizon memory.
Short-horizon precision.
CFG-1 is an autoregressive model designed for the structure of real-world manipulation: tasks that unfold over minutes, with actions that demand sub-second accuracy.
3-minute native memory
Long-horizon context window captures full task structure — pick, place, recover, repeat — without losing track of what came before.
Sliding-window precision
A short window of recent frames drives high-resolution action prediction — micrometer-level accuracy where it matters, every step.
Edge-deployable
2B parameters, optimized for under-50ms inference on a single RTX 5090. Runs on-prem, in the factory, without cloud round-trips.
Performance
From task description to working model.
Fine-tune, evaluate, refine — a task description becomes a deployable policy in a few iterations.
80%+
Task success rate
Reached with just 1 hour of task-specific teleop data, fine-tuned on CFG-1.
24h
Task adaptation cycle
Collect today, train overnight, deploy the next day.
Research
Research & publications.
We publish technical previews, evaluation notes, and field reports as CFG-1 evolves.
CFG-1, in production.
CFG-1 powers every Config Loop deployment — from feasibility test to live operation. See how it deploys on your robot.