MODEL PROFILE

Qwen-Image-2.1-NVFP4

BennyDaBall · Qwen-Image-2.1-NVFP4

**This is an independent NVFP4 quantization of Qwen Image 2.1. The Qwen team created the original model.** The original model and architecture are Qwen's work. I converted the official Comfy-Org/Qwen-Image-2.1 BF16 checkpoint package and packaged the quantized weights, workflows, and validation here. This is not a new base model or an official Qwen release. I converted Qwen Image 2.1's image transformer and Qwen3-VL 8B language encoder directly from the official BF16 weights into native ComfyUI NVFP4. The vision tower, embeddings, output head, critical image-model tensors, and VAE stay BF16. Real Blackwell FP4 kernels in both denoising and text conditioning, with an included small runtime patch for the latter. No new nodes. **RTX 5090: 6.746 s median for a complete 1024×1024, 40-step run** versus 15.629 s with BF16 and 7.553 s with official INT8. Three warm runs per variant, every node executed, including text encoding. This one-prompt benchmark used the encoder patch; full method and limits.

Image generationlicense:other
Context windowNot disclosed
Input → OutputText → Image
Model weightsNot verified
Profile updated2026/11/2 19:16:25
OVERVIEW

Model overview

**This is an independent NVFP4 quantization of Qwen Image 2.1. The Qwen team created the original model.** The original model and architecture are Qwen's work. I converted the official Comfy-Org/Qwen-Image-2.1 BF16 checkpoint package and packaged the quantized weights, workflows, and validation here. This is not a new base model or an official Qwen release. I converted Qwen Image 2.1's image transformer and Qwen3-VL 8B language encoder directly from the official BF16 weights into native ComfyUI NVFP4. The vision tower, embeddings, output head, critical image-model tensors, and VAE stay BF16. Real Blackwell FP4 kernels in both denoising and text conditioning, with an included small runtime patch for the latter. No new nodes. **RTX 5090: 6.746 s median for a complete 1024×1024, 40-step run** versus 15.629 s with BF16 and 7.553 s with official INT8. Three warm runs per variant, every node executed, including text encoding. This one-prompt benchmark used the encoder patch; full method and limits.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

许可证:other。模型介绍与第三方评测均以原来源的具体版本和方法为准。