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版本类型
类型工作流
功能文生图
格式gguf
作者David

Qwen-Image 8步 文生图片 GGUF

注意:以下所有模型文件及自定义节点,须在客户端中下载,如果没有客户端,前往下载 >>>

Qwen-Image 是通义千问系列中首个图像生成基础模型,于 2025 年 8 月发布。它拥有 200 亿参数,在文本渲染、图像生成和编辑等方面表现卓越。其擅长中英文多行段落级高保真文本渲染,对复杂场景和细粒度细节处理能力强,能精准呈现文本内容。在多个公开基准测试中,该模型取得了最先进的性能,尤其在中文文本渲染方面大幅领先现有模型。此外,它支持多种风格的图像生成以及专业级的图像编辑操作,为图像创作提供了强大助力。

模型文件
自定义节点
名称大小本地存放目录
qwen-image-Q2_K.gguf7.06 GBunet
qwen-image-Q3_K_S.gguf8.95 GBunet
qwen-image-Q3_K_M.gguf9.68 GBunet
qwen-image-Q4_0.gguf11.85 GBunet
qwen-image-Q4_K_S.gguf12.14 GBunet
qwen-image-Q4_1.gguf12.84 GBunet
qwen-image-Q4_K_M.gguf13.07 GBunet
qwen-image-Q5_K_S.gguf14.12 GBunet
qwen-image-Q5_0.gguf14.40 GBunet
qwen-image-Q5_K_M.gguf14.93 GBunet
qwen-image-Q5_1.gguf15.39 GBunet
qwen-image-Q6_K.gguf16.82 GBunet
qwen-image-Q8_0.gguf21.76 GBunet
qwen-image-BF16.gguf40.87 GBunet
名称大小本地存放目录
Qwen-Image-Lightning-4steps-V2.0.safetensors1.70 GBloras
Qwen-Image-Lightning-4steps-V2.0-bf16.safetensors850 MBloras
Qwen-Image-Lightning-4steps-V1.0.safetensors1.70 GBloras
Qwen-Image-Lightning-8steps-V1.0.safetensors1.70 GBloras
Qwen-Image-Lightning-8steps-V1.1.safetensors1.70 GBloras
Qwen-Image-Lightning-4steps-V1.0-bf16.safetensors849.61 MBloras
Qwen-Image-Lightning-8steps-V1.1-bf16.safetensors849.61 MBloras
qwen_image_vae >1 个文件
名称大小本地存放目录
qwen_image_vae.safetensors253.81 MBvae
名称大小本地存放目录
Qwen2.5-VL-7B-Instruct-UD-IQ1_S.gguf2.07 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-IQ1_M.gguf2.20 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-IQ2_XXS.gguf2.40 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-IQ2_M.gguf2.86 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q2_K.gguf3.02 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q2_K_L.gguf3.14 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-IQ3_XXS.gguf3.17 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-Q2_K_XL.gguf3.24 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q3_K_S.gguf3.49 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q3_K_M.gguf3.81 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-Q3_K_XL.gguf4.00 GBtext_encoders
Qwen2.5-VL-7B-Instruct-IQ4_XS.gguf4.24 GBtext_encoders
Qwen2.5-VL-7B-Instruct-IQ4_NL.gguf4.44 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q4_0.gguf4.44 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q4_K_S.gguf4.46 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q4_K_M.gguf4.68 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-Q4_K_XL.gguf4.79 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q4_1.gguf4.87 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q5_K_S.gguf5.32 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q5_K_M.gguf5.44 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-Q5_K_XL.gguf5.46 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q6_K.gguf6.25 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-Q6_K_XL.gguf6.96 GBtext_encoders
Qwen2.5-VL-7B-Instruct-Q8_0.gguf8.10 GBtext_encoders
Qwen2.5-VL-7B-Instruct-UD-Q8_K_XL.gguf10.19 GBtext_encoders
Qwen2.5-VL-7B-Instruct-BF16.gguf15.24 GBtext_encoders