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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.

Parameters: Steps: 20| Size: 1024x1024| Seed: 1931701040| CFG scale: 6| App: SD.Next| Version: 34031f5| Pipeline: WanPipeline| Operations: txt2img| Model: Wan2.1-T2V-1.3B-Diffusers

Execution: Time: 3m 54.34s | total 439.88 pipeline 233.25 preview 194.33 te 5.20 offload 5.07 vae 1.20 decode 0.80 post 0.27 gc

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CFG4

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CFG6

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CFG8

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CFG10

System info

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Negative: Vibrant colors, overexposed, static, blurry details, subtitles, style, artwork, painting, image, still, overall grayish, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, distorted limbs, fingers fused together, static image, cluttered background, three legs, many people in the background, walking backwards.

Parameters: Steps: 32| Size: 1024x1024| Seed: 4075624134| CFG scale: 4| App: SD.Next| Version: 7644432| Pipeline: WanPipeline| Operations: txt2img| Model: Wan2.2-TI2V-5B-Diffusers

285H Time: 1m 51.81s | total 113.45 pipeline 111.76 te 1.38 | GPU 29768 MB 24% | RAM 38.76 GB 31%

System info

app: sdnext.git updated: 2025-12-06 hash: 764443213 url: https://github.com/liutyi/sdnext/tree/pytorch
arch: x86_64 cpu: x86_64 system: Linux release: 6.17.0-7-generic
python: 3.12.3 Torch 2.9.1+xpu
ram: free:114.91 used:8.17 total:123.07
device: Intel(R) Arc(TM) Graphics (1) ipex: 
xformers: diffusers: 0.36.0.dev0 transformers: 4.57.1
active: xpu dtype: torch.bfloat16 vae: torch.bfloat16 unet: torch.bfloat16
base: Diffusers/Wan-AI/Wan2.2-TI2V-5B-Diffusers [b8fff7315c] refiner: none vae: none te: none unet: none

Config

{
  "diffusers_version": "a1f36ee3ef4ae1bf98bd260e539197259aa981c1",
  "sd_model_checkpoint": "Diffusers/Wan-AI/Wan2.2-TI2V-5B-Diffusers [b8fff7315c]",
  "diffusers_offload_mode": "none",
  "ui_request_timeout": 300000,
  "huggingface_token": "hf_..FraU",
  "sd_checkpoint_hash": null,
  "model_wan_stage": "combined"
}

Model info

Diffusers/Wan-AI/Wan2.2-TI2V-5B-Diffusers [b8fff7315c]

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Config
 Code Block
{

}
Model info
Module
Class
Device
Dtype
Quant
Params
Modules
Config
vae
AutoencoderKLWan
xpu:0
torch.bfloat16
None
704688668
272
FrozenDict({'base_dim': 160, 'decoder_base_dim': 256, 'z_dim': 48, 'dim_mult': [1, 2, 4, 4], 'num_res_blocks': 2, 'attn_scales': [], 'temperal_downsample': [False, True, True], 'dropout': 0.0, 'latents_mean': [-0.2289, -0.0052, -0.1323, -0.2339, -0.2799, 0.0174, 0.1838, 0.1557, -0.1382, 0.0542, 0.2813, 0.0891, 0.157, -0.0098, 0.0375, -0.1825, -0.2246, -0.1207, -0.0698, 0.5109, 0.2665, -0.2108, -0.2158, 0.2502, -0.2055, -0.0322, 0.1109, 0.1567, -0.0729, 0.0899, -0.2799, -0.123, -0.0313, -0.1649, 0.0117, 0.0723, -0.2839, -0.2083, -0.052, 0.3748, 0.0152, 0.1957, 0.1433, -0.2944, 0.3573, -0.0548, -0.1681, -0.0667], 'latents_std': [0.4765, 1.0364, 0.4514, 1.1677, 0.5313, 0.499, 0.4818, 0.5013, 0.8158, 1.0344, 0.5894, 1.0901, 0.6885, 0.6165, 0.8454, 0.4978, 0.5759, 0.3523, 0.7135, 0.6804, 0.5833, 1.4146, 0.8986, 0.5659, 0.7069, 0.5338, 0.4889, 0.4917, 0.4069, 0.4999, 0.6866, 0.4093, 0.5709, 0.6065, 0.6415, 0.4944, 0.5726, 1.2042, 0.5458, 1.6887, 0.3971, 1.06, 0.3943, 0.5537, 0.5444, 0.4089, 0.7468, 0.7744], 'is_residual': True, 'in_channels': 12, 'out_channels': 12, 'patch_size': 2, 'scale_factor_temporal': 4, 'scale_factor_spatial': 16, '_class_name': 'AutoencoderKLWan', '_diffusers_version': '0.35.0.dev0', 'clip_output': False, '_name_or_path': '/mnt/models/Diffusers/models--Wan-AI--Wan2.2-TI2V-5B-Diffusers/snapshots/b8fff7315c768468a5333511427288870b2e9635/vae'})
text_encoder
UMT5EncoderModel
xpu:0
torch.bfloat16
None
5680910336
486
UMT5Config { "architectures": [ "UMT5EncoderModel" ], "classifier_dropout": 0.0, "d_ff": 10240, "d_kv": 64, "d_model": 4096, "decoder_start_token_id": 0, "dense_act_fn": "gelu_new", "dropout_rate": 0.1, "dtype": "bfloat16", "eos_token_id": 1, "feed_forward_proj": "gated-gelu", "initializer_factor": 1.0, "is_encoder_decoder": true, "is_gated_act": true, "layer_norm_epsilon": 1e-06, "model_type": "umt5", "num_decoder_layers": 24, "num_heads": 64, "num_layers": 24, "output_past": true, "pad_token_id": 0, "relative_attention_max_distance": 128, "relative_attention_num_buckets": 32, "scalable_attention": true, "tie_word_embeddings": false, "tokenizer_class": "T5Tokenizer", "transformers_version": "4.57.1", "use_cache": true, "vocab_size": 256384 }
tokenizer
T5TokenizerFast
None
None
None
0
0
None
transformer
WanTransformer3DModel
xpu:0
torch.bfloat16
None
4999787712
858
FrozenDict({'patch_size': [1, 2, 2], 'num_attention_heads': 24, 'attention_head_dim': 128, 'in_channels': 48, 'out_channels': 48, 'text_dim': 4096, 'freq_dim': 256, 'ffn_dim': 14336, 'num_layers': 30, 'cross_attn_norm': True, 'qk_norm': 'rms_norm_across_heads', 'eps': 1e-06, 'image_dim': None, 'added_kv_proj_dim': None, 'rope_max_seq_len': 1024, 'pos_embed_seq_len': None, '_class_name': 'WanTransformer3DModel', '_diffusers_version': '0.35.0.dev0', '_name_or_path': 'Wan-AI/Wan2.2-TI2V-5B-Diffusers'})
schedulerUniPCMultistepScheduler
UniPCMultistepScheduler
None
None
None
0
0
FrozenDict({'num_train_timesteps': 1000, 'beta_start': 0.0001, 'beta_end': 0.02, 'beta_schedule': 'linear', 'trained_betas': None, 'solver_order': 2, 'prediction_type': 'flow_prediction', 'thresholding': False, 'dynamic_thresholding_ratio': 0.995, 'sample_max_value': 1.0, 'predict_x0': True, 'solver_type': 'bh2', 'lower_order_final': True, 'disable_corrector': [], 'solver_p': None, 'use_karras_sigmas': False, 'use_exponential_sigmas': False, 'use_beta_sigmas': False, 'use_flow_sigmas': True, 'flow_shift': 5.0, 'timestep_spacing': 'linspace', 'steps_offset': 0, 'final_sigmas_type': 'zero', 'rescale_betas_zero_snr': False, 'use_dynamic_shifting': False, 'time_shift_type': 'exponential', '_class_name': 'UniPCMultistepScheduler', '_diffusers_version': '0.35.0.dev0'})
transformer_2
NoneType
None
None
None
0
0
None
boundary_ratio
NoneType
None
None
None
0
0
None
expand_timesteps
bool
None
None
None
0
0
None
...