Descriptions:
Veteran AI runs six structured tests of Baidu’s open-source ERNIE Image model in ComfyUI, benchmarking it against commercial models like Midjourney and open-source competitors including Qwen Image and Z-Image. ERNIE Image’s 8-billion-parameter architecture — paired with a 3B prompt enhancer and Flux 2-compatible text encoders and VAE — ranks above all current open-source image models on official leaderboards while falling below top commercial offerings. The video explains how to interpret the benchmark table’s “PE” (prompt enhancer on/off) notations and why the turbo vs. standard model distinction matters in practice.
The core technical comparison pits the Turbo model (8 steps, CFG 1.0, fast generation) against the standard model (50 steps recommended, CFG 4.0, significantly higher quality but slower). The host identifies a dilemma familiar to ComfyUI users — speed versus quality — and resolves it by building a mixed two-stage sampling workflow that replaces the standard sampler with an advanced sampler, allowing precise control over when each sampling regime contributes. The tradeoff: more VRAM and compute in exchange for improved results at reduced time versus the full standard pipeline.
Test categories cover photorealistic portraiture, complex text-and-image layouts (posters, storyboards, PowerPoint-style slides), character design, and advertising creative — areas where ERNIE shows notable strength. The model and workflow files are available via the official ComfyUI Hugging Face repository, and live workflow demos are hosted on RunningHub, an online ComfyUI platform the host recommends for staying current with new model releases.
📺 Source: Veteran AI · Published April 17, 2026
🏷️ Format: Tutorial Demo
