Test 1 - Bookshop



STEPS:48162032
CFG:1

2

3

4

6

8

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.

Parameters: Steps: 4| Size: 1024x1024| Seed: 1460879190| CFG scale: 8| App: SD.Next| Version: 4ef0a4d| Pipeline: CogView4Pipeline| Operations: txt2img| Model: CogView4-6B


Time: 3m 25.75s | total 213.29 pipeline 181.89 decode 16.31 move 14.83 gc 0.46 | GPU 7926 MB 6% | RAM 31.58 GB 25%


48162032
1

2

3

4

6

8


Test - legs and shoes



STEP:48162032
CFG:1

2

3

4

6

8

Samplers

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.

Parameters: Steps: 20| Size: 1024x1024| Sampler: Euler FlowMatch| Seed: 1460879190| CFG scale: 3| App: SD.Next| Version: 4ef0a4d| Pipeline: CogView4Pipeline| Operations: txt2img| Model: CogView4-6B


Time: 14m 54.43s | total 901.94 pipeline 870.41 decode 16.51 move 14.74 gc 0.47 | GPU 7928 MB 6% | RAM 31.59 GB 25%


CFG3, STEP 20

Default

Euler FlowMatch

LCM FlowMatch


DPM2a FlowMatch

DPM2++ SDE FlowMatch

DPM2++ 2S FlowMatch


DPM2 FlowMatch

DPM2++ 2M FlowMatch



DPM2++ 3M SDE FlowMatch

DPM2++ 2M SDE FlowMatch







System

app: sdnext.git updated: 2025-07-18 hash: 4ef0a4d5 url: https://github.com/vladmandic/sdnext.git/tree/dev
arch: x86_64 cpu: x86_64 system: Linux release: 6.11.0-29-generic
python: 3.12.3 Torch: 2.7.1+xpu
device: Intel(R) Arc(TM) Graphics (1) ipex: 
ram: free:123.65 used:1.68 total:125.33 
xformers:  diffusers: 0.35.0.dev0 transformers: 4.53.2
active: xpu dtype: torch.bfloat16 vae: torch.bfloat16 unet: torch.bfloat16

Model

Model: Diffusers/THUDM/CogView4-6B
Type: cogview4
Class: CogView4Pipeline
Size: 0 bytes
Modified: 2025-07-17 21:11:21


Module

Class

Device

DType

Params

Modules

Config

tokenizer

PreTrainedTokenizerFast

None

None

0

0

None

text_encoder

GlmForCausalLM

xpu:0

torch.bfloat16

9399951360

487

GlmConfig { "architectures": [ "GlmModel" ], "attention_bias": true, "attention_dropout": 0.0, "eos_token_id": [ 151329, 151336, 151338 ], "head_dim": 128, "hidden_act": "silu", "hidden_size": 4096, "initializer_range": 0.02, "intermediate_size": 13696, "max_position_embeddings": 8192, "model_type": "glm", "num_attention_heads": 32, "num_hidden_layers": 40, "num_key_value_heads": 2, "pad_token_id": 151329, "partial_rotary_factor": 0.5, "rms_norm_eps": 1.5625e-07, "rope_theta": 10000.0, "tie_word_embeddings": false, "torch_dtype": "bfloat16", "transformers_version": "4.53.2", "use_cache": true, "vocab_size": 151552 }

vae

AutoencoderKL

xpu:0

torch.bfloat16

406100643

281

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, 512, 1024, 1024], 'layers_per_block': 3, 'act_fn': 'silu', 'latent_channels': 16, 'norm_num_groups': 32, 'sample_size': 1024, 'scaling_factor': 1.0, 'shift_factor': 0.0, 'latents_mean': None, 'latents_std': None, 'force_upcast': True, 'use_quant_conv': False, 'use_post_quant_conv': False, 'mid_block_add_attention': False, '_class_name': 'AutoencoderKL', '_diffusers_version': '0.33.0.dev0', '_name_or_path': '/mnt/models/Diffusers/models--THUDM--CogView4-6B/snapshots/63a52b7f6dace7033380cd6da14d0915eab3e6b5/vae'})

transformer

CogView4Transformer2DModel

xpu:0

torch.bfloat16

6369118272

638

FrozenDict({'patch_size': 2, 'in_channels': 16, 'out_channels': 16, 'num_layers': 28, 'attention_head_dim': 128, 'num_attention_heads': 32, 'text_embed_dim': 4096, 'time_embed_dim': 512, 'condition_dim': 256, 'pos_embed_max_size': 128, 'sample_size': 128, 'rope_axes_dim': [256, 256], '_class_name': 'CogView4Transformer2DModel', '_diffusers_version': '0.33.0.dev0', '_name_or_path': 'THUDM/CogView4-6B'})

scheduler

FlowMatchEulerDiscreteScheduler

None

None

0

0

FrozenDict({'num_train_timesteps': 1000, 'shift': 1.0, 'use_dynamic_shifting': True, 'base_shift': 0.25, 'max_shift': 0.75, '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': 'linear', 'stochastic_sampling': False, '_use_default_values': ['stochastic_sampling'], '_class_name': 'FlowMatchEulerDiscreteScheduler', '_diffusers_version': '0.33.0.dev0'})

_name_or_path

str

None

None

0

0

None