The inaugural weekend. Results land on the season board.
SEE MEDIA REPORT →Choose PizzaBench on standardized hardware or Freestyle with your own robot, model and dataset. Same three challenges — separate leaderboards.
PizzaBench teams get identical stations. Freestyle teams bring their own stack. Both run the same challenges — each track has its own season leaderboard.
The inaugural weekend. Results land on the season board.
SEE MEDIA REPORT →Full 48-hour format with the Mystery Pizza championship round. Applications open now.
APPLY FOR THIS EDITION →Season finale. Dates and venue announced once the host partner is confirmed.
GET NOTIFIED →This one ends with a robot making pizza. You get a low-cost robotic arm and 48 hours to teach it how to manipulate ingredients — no hard-coded trajectories, no simulated leaderboard. Your model runs on the physical robot.
Pizza is the theme.
Physical AI is the challenge.
You will touch the complete embodied-AI stack: robot → teleoperation → dataset → policy → inference → evaluation.
Teleoperate the SO-101 with a leader arm and show it how the task is done.
Turn episodes into a real LeRobot dataset — frames, states, actions, task text.
Fine-tune SmolVLA, ACT or a diffusion policy on GPU compute we provide.
Run inference on the physical arm. It either picks the pepperoni or it doesn't.
Standardized evaluation, then a hidden generalization challenge you cannot train for.
PizzaBench is the main cup on standardized hardware. Freestyle is for teams and startups with their own robots, models and datasets. Both are judged on the same three challenges — with separate leaderboards.
Assigned SO-101 or ElRobot station, fixed camera, starter repo. Scores count toward the season PizzaBench leaderboard and PizzaBench Champion.
CUSTOM GRIPPERS WELCOMEYour robot, your policy, your data. Same three challenges and scoring rubric — ranked on a separate Freestyle leaderboard.
CUSTOM GRIPPERS WELCOME
Pick individual pepperoni from the bin and place them accurately on marked target areas. Six pieces, one time limit.
"Make a pizza with four pepperoni and three mushrooms." Identify, count, sequence — and stop when the recipe is complete.
Revealed after models are frozen. New layout, new recipe, shifted bins. No new demonstrations. This one decides each track's leaderboard.
Sunday 15:00: the Mystery Pizza configuration is revealed. Models are already frozen. One policy, one shot, an environment your robot has never seen in exactly this arrangement.
Can your policy generalize?
No robotics experience required. Every team gets a known-working reference pipeline, so there is always a path to a functioning autonomous policy.
Friday you meet the robot. Saturday you fail and improve. Sunday the models are frozen.
ML engineers, robotics engineers, computer-vision people, researchers, students, founders and builders. Python and a bit of PyTorch go a long way; everything robot-specific is taught on Friday night.
Run your own Robot Pizza Hackathon. Gather your club, community or lab for a weekend, put a robot arm on the table and teach it to make pizza. You bring the room and the crowd. We bring the challenge, the rules and a LeRobot starter repo, so every city plays the same game.
A space, a crowd of curious builders, and some robot gear if you have it.
The three Robot Pizza Cup challenges, scoring rules, starter repo and practice simulation.
Not sure yet? Tell us what you have. "Nothing yet" is a fine answer.
No. We provide the robot stack, a Friday-night workshop, tutorials and a reference implementation that already works end to end.
No. Every team is assigned an identical SO-101 or ElRobot station with teleoperation hardware and a fixed camera.
Yes, provided it satisfies the competition interface and safety requirements. SmolVLA, ACT and diffusion policies are all supported paths.
You may build supporting infrastructure, but the scored autonomous behaviour must satisfy the published competition policy. The Mystery Pizza round is designed to expose memorized trajectories.
Scored benchmarking uses standardized reusable rigid props so runs are comparable. The live showcase after benchmarking can use edible ingredients.
Why no sauce or dough? Deformable-material and fluid manipulation would sharply increase failure risk for an inaugural event. Future editions can add them.
You keep your code. Dataset licensing and contribution terms are published before registration opens, and public contribution is opt-in.
YOUR NEXT MODEL DOESN'T ANSWER QUESTIONS. IT MOVES THINGS.
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