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Prompt: Model name text 'LongCat-Image" made by polished marbles with LongCat-Image logo on background

Parameters: Steps: 50| Size: 1024x1024| Seed: 678545279| CFG scale: 4| App: SD.Next| Version: c53ebca| Pipeline: LongCatImagePipeline| Operations: txt2img| Model: LongCat-Image
processing | 423.1/15.1s

285H Time: 8m 2.08s | total 484.49 pipeline 480.23 te 1.98 decode 1.81 gc 0.43 | GPU 31740 MB 25% | RAM 47.39 GB 39%

Info

https://github.com/meituan-longcat/LongCat-Image

https://huggingface.co/meituan-longcat/LongCat-Image

Special Handling for Text Rendering

For both Text-to-Image and Image Editing tasks involving text generation, you must enclose the target text within single or double quotation marks (both English '...' / "..." and Chinese ‘...’ / “...” styles are supported).

Reasoning: The model utilizes a specialized character-level encoding strategy specifically for quoted content. Failure to use explicit quotation marks prevents this mechanism from triggering, which will severely compromise the text rendering capability.

import torch
from diffusers import LongCatImagePipeline

if __name__ == '__main__':
    device = torch.device('cuda')

    pipe = LongCatImagePipeline.from_pretrained("meituan-longcat/LongCat-Image", torch_dtype= torch.bfloat16 )
    # pipe.to(device, torch.bfloat16)  # Uncomment for high VRAM devices (Faster inference)
    pipe.enable_model_cpu_offload()  # Offload to CPU to save VRAM (Required ~17 GB); slower but prevents OOM

    prompt = '一个年轻的亚裔女性,身穿黄色针织衫,搭配白色项链。她的双手放在膝盖上,表情恬静。背景是一堵粗糙的砖墙,午后的阳光温暖地洒在她身上,营造出一种宁静而温馨的氛围。镜头采用中距离视角,突出她的神态和服饰的细节。光线柔和地打在她的脸上,强调她的五官和饰品的质感,增加画面的层次感与亲和力。整个画面构图简洁,砖墙的纹理与阳光的光影效果相得益彰,突显出人物的优雅与从容。'
    
    image = pipe(
        prompt,
        height=768,
        width=1344,
        guidance_scale=4.0,
        num_inference_steps=50,
        num_images_per_prompt=1,
        generator=torch.Generator("cpu").manual_seed(43),
        enable_cfg_renorm=True,
        enable_prompt_rewrite=True
    ).images[0]

    image.save('./t2i_example.png')

Test 0 - Different seed variations

Prompt: photorealistic girl in bookshop choosing the book in romantic stories shelf. smiling

Prompt: Create a close-up photograph of a woman's face and hand, with her hand raised to her chin. She is wearing a white blazer and has a gold ring on her finger. Her nails are neatly manicured and her hair is pulled back into a low bun. She is smiling and has a radiant expression on her face. The background is a plain light gray color. The overall mood of the photo is elegant and sophisticated. The photo should have a soft, natural light and a slight warmth to it. The woman's hair is dark brown and pulled back into a low bun, with a few loose strands framing her face.

Prompt: Generate a photo of a woman's legs, with her feet crossed and wearing white high-heeled shoes with ribbons tied around her ankles. The shoes should have a pointed toe and a stiletto heel. The woman's legs should be smooth and tanned, with a slight sheen to them. The background should be a light gray color. The photo should be taken from a low angle, looking up at the woman's legs. The ribbons should be tied in a bow shape around the ankles. The shoes should have a red sole. The woman's legs should be slightly bent at the knee.


CFG4, STEP50Seed: 1620085323Seed:1931701040Seed:4075624134Seed:2736029172
bookshop girl



hand and face



legs and shoes




Test 1 - Bookshop

Prompt: photorealistic girl in bookshop choosing the book in romantic stories shelf. smiling




48163250
CFG1




CFG2




CFG3




CFG4




CFG5




CFG6




CFG8




Test 2 - Face and hand

Prompt: Create a close-up photograph of a woman's face and hand, with her hand raised to her chin. She is wearing a white blazer and has a gold ring on her finger. Her nails are neatly manicured and her hair is pulled back into a low bun. She is smiling and has a radiant expression on her face. The background is a plain light gray color. The overall mood of the photo is elegant and sophisticated. The photo should have a soft, natural light and a slight warmth to it. The woman's hair is dark brown and pulled back into a low bun, with a few loose strands framing her face.



816203250
CFG1




CFG2




CFG3




CFG4




CFG5




CFG6




CFG7




Test 3 - Legs

Prompt: Prompt: Generate a photo of a woman's legs, with her feet crossed and wearing white high-heeled shoes with ribbons tied around her ankles. The shoes should have a pointed toe and a stiletto heel. The woman's legs should be smooth and tanned, with a slight sheen to them. The background should be a light gray color. The photo should be taken from a low angle, looking up at the woman's legs. The ribbons should be tied in a bow shape around the ankles. The shoes should have a red sole. The woman's legs should be slightly bent at the knee.




8163264
CFG2



CFG4



CFG6



CFG8



CFG10



Test 4 - Empty prompts


1024x1024, Steps 50


seed 1


seed 2


seed 3


seed 4


seed 5


seed 6


seed 7


seed 8


seed 9


seed 10


seed 21


seed 38


seed 42

 

sweed 68


seed 2025

Test 5 - Other Models cover


Test 6 - Art Prompts


System info



Config

{

}


Model info


ModuleClassDeviceDtypeQuantParamsModulesConfig
vaeAutoencoderKLxpu:0torch.bfloat16None83819683241

FrozenDict({'in_channels': 3, 'out_channels': 3, 'down_block_types': ['DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D', 'DownEncoderBlock2D'], 'up_block_types': ['UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBlock2D', 'UpDecoderBlock2D'], 'block_out_channels': [128, 256, 512, 512], 'layers_per_block': 2, 'act_fn': 'silu', 'latent_channels': 16, 'norm_num_groups': 32, 'sample_size': 1024, 'scaling_factor': 0.3611, 'shift_factor': 0.1159, 'latents_mean': None, 'latents_std': None, 'force_upcast': True, 'use_quant_conv': False, 'use_post_quant_conv': False, 'mid_block_add_attention': True, '_class_name': 'AutoencoderKL', '_diffusers_version': '0.30.0.dev0', '_name_or_path': '/mnt/models/Diffusers/models--meituan-longcat--LongCat-Image/snapshots/d2ea50b79a930074c37b9b97ce45e3b2ea8cf4d8/vae'})

text_encoderQwen2_5_VLForConditionalGenerationxpu:0torch.bfloat16None8292166656763

Qwen2_5_VLConfig { "architectures": [ "Qwen2_5_VLForConditionalGeneration" ], "attention_dropout": 0.0, "bos_token_id": 151643, "dtype": "bfloat16", "eos_token_id": 151645, "hidden_act": "silu", "hidden_size": 3584, "initializer_range": 0.02, "intermediate_size": 18944, "max_position_embeddings": 128000, "max_window_layers": 28, "model_type": "qwen2_5_vl", "num_attention_heads": 28, "num_hidden_layers": 28, "num_key_value_heads": 4, "rms_norm_eps": 1e-06, "rope_scaling": { "mrope_section": [ 16, 24, 24 ], "rope_type": "default", "type": "default" }, "rope_theta": 1000000.0, "sliding_window": 32768, "text_config": { "_name_or_path": "hunyuanvideo-community/HunyuanImage-2.1-Diffusers", "architectures": [ "Qwen2_5_VLForConditionalGeneration" ], "attention_dropout": 0.0, "bos_token_id": 151643, "dtype": "bfloat16", "eos_token_id": 151645, "hidden_act": "silu", "hidden_size": 3584, "image_token_id": 151655, "initializer_range": 0.02, "intermediate_size": 18944, "layer_types": [ "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention", "full_attention" ], "max_position_embeddings": 128000, "max_window_layers": 28, "model_type": "qwen2_5_vl_text", "num_attention_heads": 28, "num_hidden_layers": 28, "num_key_value_heads": 4, "rms_norm_eps": 1e-06, "rope_scaling": { "mrope_section": [ 16, 24, 24 ], "rope_type": "default", "type": "default" }, "rope_theta": 1000000.0, "sliding_window": null, "use_cache": true, "use_sliding_window": false, "video_token_id": 151656, "vision_end_token_id": 151653, "vision_start_token_id": 151652, "vision_token_id": 151654, "vocab_size": 152064 }, "tie_word_embeddings": false, "transformers_version": "4.57.3", "use_cache": true, "use_sliding_window": false, "vision_config": { "depth": 32, "dtype": "bfloat16", "fullatt_block_indexes": [ 7, 15, 23, 31 ], "hidden_act": "silu", "hidden_size": 1280, "in_channels": 3, "in_chans": 3, "initializer_range": 0.02, "intermediate_size": 3420, "model_type": "qwen2_5_vl", "num_heads": 16, "out_hidden_size": 3584, "patch_size": 14, "spatial_merge_size": 2, "spatial_patch_size": 14, "temporal_patch_size": 2, "tokens_per_second": 2, "window_size": 112 }, "vision_token_id": 151654, "vocab_size": 152064 }

tokenizerQwen2TokenizerNoneNoneNone00

None

transformerLongCatImageTransformer2DModelxpu:0torch.bfloat16None6270668864677

FrozenDict({'patch_size': 1, 'in_channels': 64, 'num_layers': 10, 'num_single_layers': 20, 'attention_head_dim': 128, 'num_attention_heads': 24, 'joint_attention_dim': 3584, 'pooled_projection_dim': 3584, 'axes_dims_rope': [16, 56, 56], '_use_default_values': ['axes_dims_rope'], '_class_name': 'LongCatImageTransformer2DModel', '_diffusers_version': '0.30.0.dev0', 'guidance_embeds': False, '_name_or_path': 'meituan-longcat/LongCat-Image'})

schedulerFlowMatchEulerDiscreteSchedulerNoneNoneNone00

FrozenDict({'num_train_timesteps': 1000, 'shift': 3.0, 'use_dynamic_shifting': True, 'base_shift': 0.5, 'max_shift': 1.15, 'base_image_seq_len': 256, 'max_image_seq_len': 4096, 'invert_sigmas': False, 'shift_terminal': None, 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_beta_sigmas': False, 'time_shift_type': 'exponential', 'stochastic_sampling': False, '_use_default_values': ['shift_terminal', 'stochastic_sampling', 'time_shift_type', 'use_exponential_sigmas', 'use_karras_sigmas', 'use_beta_sigmas', 'invert_sigmas'], '_class_name': 'FlowMatchEulerDiscreteScheduler', '_diffusers_version': '0.30.0.dev0'})

text_processorQwen2VLProcessorNoneNoneNone00

None



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