I Made Fusion and Qwen3.6 27B Build the Same Web App
I put OpenRouter Fusion and Qwen3.6 27B head-to-head and gave them the exact same prompt: build the same web app from scratch. Same goal. Same constraints. Same phased build. Very different results. In this video, I compare how a multi-model AI committee stacks up against a single 27B model when the task is actual software delivery, not just talking about code. The project was a real web app built in phases on fresh Linux VPSes, with each model responsible for turning the prompt into something usable. This wasn’t about benchmark scores or cherry-picked one-liners. I wanted to see which one could actually plan, build, adapt, and ship. For all prompts, code outputs, and info about the video, visit: https://tokenchaser.net Drop a comment with which models you want to see go head-to-head next.
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# Phase 1 — Core Player You're on a fresh Ubuntu VPS. Install whatever dependencies you need. Build and deploy a web-based music player accessible on the local network at port 80. ## What to build - **Drag & drop MP3 upload** — files go into a shared library, persisted to disk - **Synced playback** — pause/play/seek on one device updates all connected browsers - **Playlist manager** — create, rename, delete playlists, add/remove tracks - **Crossfader** — smooth fade between tracks, adjustable 0–10s - **Waveform scrubber** — click to seek, drag to set loop points - **Frequency bar visualizer** — real-time audio visualization ## Tech Your choice. Node.js or Python backend. WebSockets for sync. TypeScript frontend if you want. Whatever ships fast. ## Deploy - Port 80, accessible at http://[VPS_IP] - Auto-start on boot via systemd - Persist uploaded files to disk Build it. Deploy it. Make it work.
# Phase 2 — Library & Control Phase 1 is deployed and working. Extend it with these features. ## What to build - **YouTube link support** — paste a URL, joins the queue, plays in sync - **Speed/pitch control** — adjust playback speed without killing pitch - **Request queue** — connected users browse library, vote on next track - **Hot cues** — mark positions in a track, trigger instantly from the UI - **Mixer panel** — overlay drums, beats, reverb, delay, EQ on the playing track. Adjustable volume per layer - **3+ visualizer modes** — keep frequency bars, add circular spectrum and particle effects - **Theme selector** — dark, neon, pastel ## Deploy - Same port 80, same auto-start, same persistent storage - Extend the existing codebase Build it. Deploy it. Make it work.
# Phase 3 — Polish & Intelligence Phase 2 is deployed and working. Add the finishing touches. ## What to build - **Auto-mix** — crossfade to next track when current one ends, BPM-aware beatmatching if possible - **Scheduled playback** — set times of day for playlists to auto-start - **AirPlay casting** — cast audio + visualizer to an AirPlay receiver on the network - **Mood selector** — pick a mood (chill, party, focus, workout), auto-generates a playlist from the library based on tempo/energy - **Multi-room support** — group devices into rooms, play different playlists in different rooms ## Deploy - Same port 80, same auto-start, same persistent storage - Extend the existing codebase Build it. Deploy it. Make it work.