What a humanoid can really do in your kitchen today

The setting

The kitchen is where a home robot would earn its keep and where it could do the most damage. It is full of jobs people would happily hand off, such as unloading the dishwasher, wiping counters and prepping ingredients. It is also full of hot surfaces, sharp edges, breakable glass and food that goes wrong if you get the timing wrong.

It is also the room robot makers most like to film. Over 2026, humanoids and robot arms have been shown loading dishwashers, flipping pancakes, working air fryers and brewing coffee. We lined those demos up against the actual work of running a kitchen to see how much of it is covered.

What a humanoid would need to do

We split kitchen help into five kinds of work, from easiest to hardest:

1. Put things where they go. Unload a dishwasher, store groceries, clear a table.
2. Run appliances. Open, load, set and start a dishwasher, microwave, air fryer or kettle.
3. Handle food. Pour, scoop, flip, open packets, seal bags.
4. Cook. Follow a recipe with heat and timing, and notice when something is burning.
5. Clean up. Wipe spills, scrub pans, take out the rubbish.

All five need the robot to work safely next to people, in a room it did not design, with objects it has not seen before.

What has actually been demonstrated

A full dishwasher cycle, once, on video. In January 2026, Figure showed Helix 02 unloading and reloading a dishwasher across a full-sized kitchen, then starting it. Figure calls it "a four-minute, end-to-end autonomous task that integrates walking, manipulation, and balance with no resets and no human intervention," made up of 61 separate actions. Figure did not publish how many attempts it took or how often the task succeeds. The same post showed fine-grained skills such as unscrewing a bottle cap and dispensing exactly 5 ml from a syringe, and Figure said plainly that "the results are early."

An appliance it had barely seen. Physical Intelligence says its π0.7 model operated an air fryer with only two related clips in its training data. The catch is in how it got there. Without guidance the attempt failed; with step-by-step spoken coaching it worked, and one air-fryer test went from 5% to 95% success after about 30 minutes of refining the instructions. A Physical Intelligence researcher told TechCrunch: "You can't tell it, 'Hey, go make me some toast'."

Cooking-adjacent tasks from one video. Skild AI says its S1 model learned tasks including pancake flipping and pour-over coffee from a single first-person video of a person, with no retraining. Skild reports 66% success on unseen tasks, which NVIDIA describes as a per-step rate. Skild did not say which robot hardware it used.

Soft, fiddly packaging. Google DeepMind says Gemini Robotics 2 can drive a five-fingered hand on Apptronik's Apollo 2 humanoid to tie knots and seal a ziplock bag. DeepMind's published numbers show where the edge is: tying a trash bag succeeded 44% of the time, and picking an object up from the floor 45.7%.

The gap

Against our five kinds of work, the record looks like this.

• Putting things away is the most advanced. The dishwasher demo covers it end to end, but it is one run in one kitchen with no published success rate. Figure's newer Helix 2.5 shows chores carrying over to 30 unfamiliar homes at 56% full-task success, but none of its three test chores was in the kitchen.
• Running appliances works with help. The air-fryer result is real progress, but it needed a person to talk the robot through it. That is closer to supervising a new helper than to handing off a job.
• Handling food has good demos and weak numbers. Pancakes, coffee and bags have all been shown; the success rates we can see run from under half to about two in three per step.
• Cooking a meal, with heat and timing and judgement, has not been demonstrated in any source we found.
• Cleaning is almost untested in public. We found no measured results for wiping counters or scrubbing pans with a humanoid.

Two more gaps sit across all five. The first is safety. None of these posts reports how the robots behave around a hot hob, a knife or a child reaching in. DeepMind has introduced a safety benchmark, ASIMOV-Agentic, but we have not seen independent results. The second is breakage. Real kitchens have glass and ceramic, and a humanoid that succeeds half the time will drop things.

Our read: a humanoid in your kitchen in the next few years looks like a dishwasher unloader and a tidier, with appliances run under supervision. Cooking is a research goal, not a feature, and anyone selling it today should be able to show you the success rate.