This week, Reddit's LocalLLaMA community ran what looks like a frivolous test: having 5 LLMs each produce an HTML file that animates a soap dispenser (the pump you press to release hand soap) in action. Behind the itch-to-try impulse is a serious point: putting "AI writing frontend code"—an increasingly everyday task—onto a problem surface that mirrors daily life.
What this is
The test was launched by user Foxiya on r/LocalLLaMA, with one rule: output a complete HTML file that plays the full process of pressing the dispenser to release liquid and the mechanism springing back. The five competing models: Opus 5.5 (high-reasoning tier), DeepSeek V4.1 Flash, Qwen 3.8 Max, ChatGPT 5.6 Sol (high-reasoning tier), and Opus 5 (high-reasoning tier).
Results were presented as side-by-side videos, with no unified scoring—left to the comment section to vote. We observed several patterns: the two Chinese models kept close on animation fluidity and physical logic, with no obvious falling behind; meanwhile, high-reasoning tiers did not pull the kind of gap over standard tiers that vendors' marketing implies.
Industry view
Many developers back these "everyday problem" tests. The top comment on the original post reads, "We don't need AI to win gold medals—we need it to write us a working page." In their view, if AI coding can't get a soap-pump animation right, hyping Agents (AI that can autonomously execute multi-step tasks) is meaningless—basic tactile feel doesn't pass, and no amount of story-telling on top makes it stable.
But there are cooler voices among practitioners. A long-time model evaluation watcher cautioned that single-question assessments can't reflect comprehensive engineering capability—HTML animation is essentially a "moves-or-not" visual judgment with heavy subjective weight. The more realistic view: it's an interesting mirror, but not a selection basis. Don't treat community votes as your boss's procurement reference.
Impact on regular people
For enterprise IT: Agent-class benchmarks are now too numerous to track. What actually separates models during procurement is the ability to land "one-line business requirements"—we recommend thickening the "real small tasks" portion of your evaluation list.
For individual careers: The bar for non-programmers writing a simple webpage, product motion, or PPT animation is dropping fast. What separates output is shifting from "can you code" to "can you ask clearly."
For consumer markets: Personal AI assistants are transitioning from "Q&A tools" to "make-things" mode. Over the next year, mainstream products will likely roll out "one-line-to-mini-app" features in succession.