Info
https://huggingface.co/tencent/HunyuanImage-2.1
https://github.com/Tencent-Hunyuan/HunyuanImage-2.1/tree/main
# Examples of supported resolutions and aspect ratios for HunyuanImage-2.1:
# 16:9 -> width=2560, height=1536
# 4:3 -> width=2304, height=1792
# 1:1 -> width=2048, height=2048
# 3:4 -> width=1792, height=2304
# 9:16 -> width=1536, height=2560
# Please use one of the above width/height pairs for best results.
width=2048,
height=2048,
use_reprompt=False, # Enable prompt enhancement (which may result in higher GPU memory usage)
use_refiner=True, # Enable refiner model
# For the distilled model, use 8 steps for faster inference.
# For the non-distilled model, use 50 steps for better quality.
num_inference_steps=8 if "distilled" in model_name else 50,
guidance_scale=3.25 if "distilled" in model_name else 3.5,
shift=4 if "distilled" in model_name else 5,
seed=649151,
1024 vs 2048
| 1024 | 2048 |
|---|---|
Prompt: A cute, cartoon-style anthropomorphic penguin plush toy with fluffy fur, standing in a painting studio, wearing a red knitted scarf and a red beret with the word “Hunyuan Image” on it, holding a paintbrush with a focused expression as it paints an oil painting of the Mona Lisa, rendered in a photorealistic photographic style. Number 17B is handwritten over the image in the top left corner. Parameters: Steps: 8| Size: 1024x1024| Seed: 32| CFG scale: 3.25| App: SD.Next| Version: 187943c| Pipeline: HunyuanImagePipeline| Operations: txt2img| Model: HunyuanImage-2.1-Distilled-Diffusers Time: 2m 0.26s | total 148.30 pipeline 120.19 callback 18.66 te 7.46 vae 1.55 move 0.36 | GPU 52678 MB 41% | RAM 84.28 GB 67% | Prompt: A cute, cartoon-style anthropomorphic penguin plush toy with fluffy fur, standing in a painting studio, wearing a red knitted scarf and a red beret with the word “Hunyuan Image” on it, holding a paintbrush with a focused expression as it paints an oil painting of the Mona Lisa, rendered in a photorealistic photographic style. Number 17B is handwritten over the image in the top left corner. Parameters: Steps: 8| Size: 2048x2048| Seed: 32| CFG scale: 3.25| App: SD.Next| Version: 187943c| Pipeline: HunyuanImagePipeline| Operations: txt2img| Model: HunyuanImage-2.1-Distilled-Diffusers Time: 5m 52.39s | total 359.75 pipeline 352.28 te 4.51 vae 1.45 callback 1.38 | GPU 59348 MB 46% | RAM 90.14 GB 72% |
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.
1024px
| CFG3.25, STEP 8 | Seed: 1620085323 | Seed:1931701040 | Seed:4075624134 | Seed:2736029172 |
|---|---|---|---|---|
bookshop girl | ||||
| hand and face | ||||
| legs and shoes |
2048px
Prompt: photorealistic girl in bookshop choosing the book in romantic stories shelf. smiling
Parameters: Steps: 8| Size: 2048x2048| Seed: 1620085323| CFG scale: 3.25| App: SD.Next| Version: 187943c| Pipeline: HunyuanImagePipeline| Operations: txt2img| Model: HunyuanImage-2.1-Distilled-Diffusers
Time: 5m 52.54s | total 355.98 pipeline 352.46 te 2.00 callback 1.37 | GPU 59348 MB 46% | RAM 90.19 GB 72%
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: 8| Size: 2048x2048| Seed: 1620085323| CFG scale: 3.25| App: SD.Next| Version: 187943c| Pipeline: HunyuanImagePipeline| Operations: txt2img| Model: HunyuanImage-2.1-Distilled-Diffusers
Time: 5m 52.51s | total 358.48 pipeline 352.44 te 4.53 callback 1.37 | GPU 59348 MB 46% | RAM 90.46 GB 72%
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: 8| Size: 2048x2048| Seed: 2736029172| CFG scale: 3.25| App: SD.Next| Version: 187943c| Pipeline: HunyuanImagePipeline| Operations: txt2img| Model: HunyuanImage-2.1-Distilled-Diffusers
Time: 6m 5.18s | total 371.20 pipeline 365.10 te 4.52 callback 1.44 | GPU 59348 MB 46% | RAM 110.0 GB 88%
| CFG3.25, STEP 8 | Seed: 1620085323 | Seed:1931701040 | Seed:4075624134 | Seed: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
| 2 | 4 | 6 | 8 | 10 | 12 | 14 | 16 | |
|---|---|---|---|---|---|---|---|---|
CFG3.25 |
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: 2048x2048| Seed: 2736029172| CFG scale: 3.25| App: SD.Next| Version: ded5afc| Pipeline: HunyuanImagePipeline| Operations: txt2img| Model: HunyuanImage-2.1-Distilled-Diffusers
Time: 4m 44.70s | total 378.10 pipeline 284.60 onload 41.82 te 21.00 vae 16.45 offload 13.42 callback 0.69 | GPU 51856 MB 40% | RAM 93.26 GB 74%
| 2 | 4 | 6 | 8 | 10 | 12 | 14 | 16 | 32 | |
|---|---|---|---|---|---|---|---|---|---|
CFG3.25 |
Test 3 - Legs
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.
| 2 | 4 | 6 | 8 | 10 | 12 | 14 | 16 | |
|---|---|---|---|---|---|---|---|---|
CFG3.25 |
Test 4 - Other model Covers
512px
1024px
2048px
Test 5 - Art Prompts
System info
Sat Oct 25 12:53:29 2025 app: sdnext.git updated: 2025-11-20 hash: 187943c3e url: https://github.com/liutyi/sdnext/tree/pytorch arch: x86_64 cpu: x86_64 system: Linux release: 6.14.0-36-generic Python: 3.12.3 Torch: 2.9.1+xpu device: Intel(R) Arc(TM) Graphics (1) ipex: ram: free:119.21 used:6.12 total:125.33 xformers: diffusers: 0.36.0.dev0 transformers: 4.57.1 active: xpu dtype: torch.bfloat16 vae: torch.bfloat16 unet: torch.bfloat16 base: hunyuanvideo-community/HunyuanImage-2.1-Distilled-Diffusers refiner: none vae: none te: none unet: none Backend: ipex Pipeline: native Memory optimization: none Cross-attention: Scaled-Dot-Product
Config
"huggingface_token": "hf_..FraU", "diffusers_version": "cd3bbe2910666880307b84729176203f5785ff7e", "sd_model_checkpoint": "hunyuanvideo-community/HunyuanImage-2.1-Distilled-Diffusers", "sd_checkpoint_hash": null, "schedulers_shift": 4, "diffusers_offload_mode": "none", "diffusers_to_gpu": true, "device_map": "gpu", "show_progress_type": "Approximate", "ui_request_timeout": 300000
Model info
hunyuanvideo-community/HunyuanImage-2.1-Distilled-Diffusers [2effeb8511]
| Module | Class | Device | Dtype | Quant | Params | Modules | Config |
|---|---|---|---|---|---|---|---|
| vae | AutoencoderKLHunyuanImage | xpu:0 | torch.bfloat16 | None | 405575491 | 255 | FrozenDict({'in_channels': 3, 'out_channels': 3, 'latent_channels': 64, 'block_out_channels': [128, 256, 512, 512, 1024, 1024], 'layers_per_block': 2, 'spatial_compression_ratio': 32, 'sample_size': 384, 'scaling_factor': 0.75289, 'downsample_match_channel': True, 'upsample_match_channel': True, '_class_name': 'AutoencoderKLHunyuanImage', '_diffusers_version': '0.36.0.dev0', '_name_or_path': '/mnt/models/Diffusers/models--hunyuanvideo-community--HunyuanImage-2.1-Distilled-Diffusers/snapshots/2effeb8511aee5b2ed94984d30c630203404173b/vae'}) |
| text_encoder | Qwen2_5_VLForConditionalGeneration | xpu:0 | torch.bfloat16 | None | 8292166656 | 763 | 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": "4.57.1", "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 } |
| tokenizer | Qwen2Tokenizer | None | None | None | 0 | 0 | None |
| text_encoder_2 | T5EncoderModel | xpu:0 | torch.bfloat16 | None | 219314944 | 235 | T5Config { "architectures": [ "T5EncoderModel" ], "classifier_dropout": 0.0, "d_ff": 3584, "d_kv": 64, "d_model": 1472, "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", "gradient_checkpointing": false, "initializer_factor": 1.0, "is_encoder_decoder": false, "is_gated_act": true, "layer_norm_epsilon": 1e-06, "model_type": "t5", "num_decoder_layers": 4, "num_heads": 6, "num_layers": 12, "pad_token_id": 0, "relative_attention_max_distance": 128, "relative_attention_num_buckets": 32, "tie_word_embeddings": false, "tokenizer_class": "ByT5Tokenizer", "transformers_version": "4.57.1", "use_cache": false, "vocab_size": 1510 } |
| tokenizer_2 | ByT5Tokenizer | None | None | None | 0 | 0 | None |
| transformer | HunyuanImageTransformer2DModel | xpu:0 | torch.bfloat16 | None | 17453334976 | 1406 | FrozenDict({'in_channels': 64, 'out_channels': 64, 'num_attention_heads': 28, 'attention_head_dim': 128, 'num_layers': 20, 'num_single_layers': 40, 'num_refiner_layers': 2, 'mlp_ratio': 4.0, 'patch_size': [1, 1], 'qk_norm': 'rms_norm', 'guidance_embeds': True, 'text_embed_dim': 3584, 'text_embed_2_dim': 1472, 'rope_theta': 256.0, 'rope_axes_dim': [64, 64], 'use_meanflow': True, '_class_name': 'HunyuanImageTransformer2DModel', '_diffusers_version': '0.36.0.dev0', '_name_or_path': 'hunyuanvideo-community/HunyuanImage-2.1-Distilled-Diffusers'}) |
| scheduler | FlowMatchEulerDiscreteScheduler | None | None | None | 0 | 0 | FrozenDict({'num_train_timesteps': 1000, 'shift': 4.0, 'use_dynamic_shifting': False, '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, '_class_name': 'FlowMatchEulerDiscreteScheduler', '_diffusers_version': '0.36.0.dev0'}) |
| guider | NoneType | None | None | None | 0 | 0 | None |
| ocr_guider | NoneType | None | None | None | 0 | 0 | None |

