Every time a model said done, no part was installed
We gave six vision-language models the same four tries on our PC assembly benchmark: install RAM or a CPU in two simulated PCs. A model ends a try by saying done. They said done 16 times. No part was installed in any of those tries. We call that a false done.
The numbers
What the models did
Two models never said done. Claude Haiku 5.5 and Gemma 4 E4B used every step and stopped. Each time, Haiku said the steps left were not enough to finish.
The other four said done in all four tries. Claude Sonnet 5.5 quit with steps left. Claude Opus 5.5 got furthest: by its own report it carried RAM modules to the slots and left them standing, unseated. It said it could not confirm seating with 256 px cameras, then said done. Molmo2-ER and Phi-4 multimodal copied the example plan in the task card, and that example ended in done.
The Claude models and the open models ran with different prompts, so compare models only within each group. How we ran it has the details.
Why false done matters
On an assembly line, done starts the next step: close the case, power on, ship. A model that stops without finishing costs a retry. A false done ships a broken machine.
All six models had a success rate of 0%, so success rate alone hides the difference between them. The benchmark records false done as its own outcome, apart from a try that just runs out of steps.
Limits
This is a pilot: 4 tries per model, two tasks, dev split. With zero successes, every done was a false done by construction, so this measures how ready a model is to say done before the task is finished. It does not measure calibration.
Haiku said done 0 of 4 times and Sonnet and Opus 8 of 8. Paired by task, that gap is not significant (sign test p = 0.125). A rerun with the current prompts is planned. All limits.
- Results by model
How each try ended, steps used and peak robot force.
- How we ran it
Setups, tasks, step budgets, prompts and the scripted reference.
- Limits
Sample size, prompt versions and what these numbers do not measure.