Local Ai
I tested Ernie Image Turbo (fp8, nvfp4, fp16 and INT8) with Nano Banana Pro 2 Prompts so you won't have to
This r/StableDiffusion post is a community-driven benchmark comparing multiple quantization formats — fp8, nvfp4, fp16, and INT8 — of Baidu's ERNIE Image Turbo text-to-image model, using a standardize
This r/StableDiffusion post is a community-driven benchmark comparing multiple quantization formats — fp8, nvfp4, fp16, and INT8 — of Baidu's ERNIE Image Turbo text-to-image model, using a standardized set of "Nano Banana Pro 2" prompts as a consistent evaluation baseline. The goal is to assess the trade-offs between image quality and performance/memory efficiency across these precision formats, sparing other users the time and compute cost of running the tests themselves. Such comparisons are common in the Stable Diffusion community, where lower-precision quantizations like fp8 and nvfp4 can significantly reduce VRAM usage and increase generation speed, but may introduce quality degradation depending on the model and hardware.
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- I found this interesting as it gives insight to how Z-image Turbo breaks down a prompt and then enhances it before image generation. Auto-translation to English included below in the text body.
Source: r/StableDiffusion | 2026-04-16