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ComfyUI Krea 2 NVFP4 Quantization Shows Slower Performance Than fp8_scaled

By PulseAugur Editorial · [1 sources] ·

A user on Reddit's r/StableDiffusion subreddit has reported that the NVFP4 quantization of the Krea 2 model, when used with ComfyUI, is significantly slower than the fp8_scaled version. The user observed this performance degradation on a 5060 Ti GPU and is seeking verification from other users, as they expected NVFP4 to offer a speed improvement, similar to its performance with the klein9b model. AI

IMPACT Potential performance bottleneck for users employing NVFP4 quantization with Krea 2 in ComfyUI.

RANK_REASON User-reported performance issue with a specific software and model quantization.

Read on r/StableDiffusion →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

ComfyUI Krea 2 NVFP4 Quantization Shows Slower Performance Than fp8_scaled

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Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
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Tool
User-reported performance issue with a specific software and model quantization.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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High
Clearly on-topic for AI-industry coverage.
Story freshness
94 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/KissMyShinyArse ·

    ComfyUI's nvfp4 quantization of Krea 2 is 2x slower than fp8_scaled

    <!-- SC_OFF --><div class="md"><p><code>krea2_turbo_nvfp4.safetensors</code> performs much worse than <code>krea2_turbo_fp8_scaled.safetensors</code> on my 5060 Ti. I'd expect NVFP4 to be at least twice as fast (which is true for klein9b), but somehow the opposite is true.</p> <p…

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