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Image Generation on LSUN Bedroom 256x256 (test)

1.88FIDTDPM+ (TTrunc=99)
0.50089.810419.1228.4296Mar 30, 2019May 10, 2020Jun 21, 2021Aug 2, 2022Sep 13, 2023Oct 24, 2024Dec 5, 2025

Evaluation results

MethodLinks
TDPM+ (TTrunc=99)Backbone=ADM, NFE=100, TTrunc=992022.021.88————
TDPM+ (TTrunc=49)Backbone=ADM, NFE=50, TTrunc=492022.021.89————
ADM#Param=552.8M, MACs=1114.2G2022.111.9————
ADMBackbone=ADM, NFE=10002022.021.9————
TDPM (TTrunc=99)Backbone=ADM, NFE=100, TTrunc=992022.022.24————
ADM+DDIMBackbone=ADM, NFE=2502022.022.31————
StyleGAN2020.062.65————
TDPM (TTrunc=49)Backbone=ADM, NFE=50, TTrunc=492022.022.92————
LDM#Param=274.1M, MACs=96.1G2022.113————
Full precisionBitwidth (W/A)=32/32, model=LDM-4, steps=200, eta=1.02023.053—7.13——
FPPrec. (W/A)=32/32, Architecture=LDM-4, Steps=100, eta=12025.053.02——2.29—
Diffusion StyleGAN22022.063.6532———
TDPM+ (TTrunc=99)Backbone=DDPM, NFE=100, TTrunc=992022.023.67————
PTQDBitwidth (W/A)=8/8, model=LDM-4, steps=200, eta=1.02023.053.75—9.89——
Q-DiffusionBitwidth (W/A)=8/8, model=LDM-4, steps=200, eta=1.02023.053.8—9.95——
TDPM (TTrunc=99)Backbone=DDPM, NFE=100, TTrunc=992022.023.95————
TDPM+ (TTrunc=49)Backbone=DDPM, NFE=50, TTrunc=492022.023.98————
StyleGAN2Backbone=GAN-based, NFE=12022.023.98————
StyleGAN22022.063.9832———
TDPM+ (TTrunc=4)Backbone=ADM, NFE=5, TTrunc=42022.024.01————
TDPM+ (TTrunc=4)Backbone=DDPM, NFE=5, TTrunc=42022.024.09————
TDPM (TTrunc=49)Backbone=DDPM, NFE=50, TTrunc=492022.024.1————
TDPM (TTrunc=4)Backbone=DDPM, NFE=5, TTrunc=42022.024.16————
IDDPM#Param=113.7M, MACs=248.6G2022.114.2————
StyleGAN2 + DiffAug2022.064.2519———
Denoising Diffusion Probabilistic Modelsloss_objective=L_simple, model_scale=large2020.064.9————
DDPM#Param=113.7M, MACs=248.7G2022.114.9————
DDPMBackbone=DDPM, NFE=10002022.024.9————
SD#Param=21.1M, MACs=6.7G2022.115.2————
TDPM (TTrunc=0)Backbone=GAN-based, NFE=1, TTrunc=02022.025.24————
PTQDBitwidth (W/A)=MP, model=LDM-4, steps=200, eta=1.02023.055.49—12.04——
Q-DiffusionBitwidth (W/A)=MP, model=LDM-4, steps=200, eta=1.02023.055.75—12.79——
PTQDBitwidth (W/A)=4/8, model=LDM-4, steps=200, eta=1.02023.055.94—15.16——
COCO-GANModel Parameters=N2,M2,S32, Convergence=Not fully converged2019.035.99————
FPModel=LDM-4, Steps=50, W/A=32/322025.056.1751.4613.92—64.3
Denoising Diffusion Probabilistic Modelsloss_objective=L_simple2020.066.36————
DDIMBackbone=DDPM, NFE=502022.026.62————
Q-DiffusionBitwidth (W/A)=4/8, model=LDM-4, steps=200, eta=1.02023.056.72—18.8——
FPBit (W/A)=32/32, Model architecture=LDM-4, Denoising steps=1002025.127.5641.1814.06—51.95
StyleGAN2-ADABackbone=GAN-based, NFE=12022.027.89————
StyleGAN2 + ADA2022.067.895———
TDPM (TTrunc=4)Backbone=ADM, NFE=5, TTrunc=42022.027.92————
PGGAN2019.038.34————
ProgressiveGAN2020.068.34————
TALORAPrec. (W/A)=6/6, h=4, Architecture=LDM-4, Steps=100, eta=12025.058.4——2.49—
TALORAPrec. (W/A)=6/6, h=2, Architecture=LDM-4, Steps=100, eta=12025.058.42——2.49—
SA-QLoRAModel=LDM-4, Steps=50, W/A=4/82025.058.7952.3112.41—50.16
IntroVAE2019.038.84————
CacheQuantCache Frequency (N)=2, Precision=W8A8, Bops=3.26T, Speedup=3.05x, Compression Ratio=3.99x, Retrain=false, T=100, eta=02025.038.85————
CacheQuantCache Frequency (N)=3, Precision=W8A8, Bops=2.34T, Speedup=4.72x, Compression Ratio=3.99x, Retrain=false, T=100, eta=02025.039.27————
EfficientDMModel=LDM-4, Steps=50, W/A=4/82025.059.3253.0214.48—48.62
SA-PTQModel=LDM-4, Steps=50, W/A=8/82025.059.8354.5413.85—56.86
Q-DiffusionPrec. (W/A)=6/6, Architecture=LDM-4, Steps=100, eta=12025.0510.1——2.11—
QuESTPrec. (W/A)=6/6, Architecture=LDM-4, Steps=100, eta=12025.0510.1——2.2—
CacheQuantCache Frequency (N)=5, Precision=W8A8, Bops=1.54T, Speedup=7.06x, Compression Ratio=3.99x, Retrain=false, T=100, eta=02025.0310.29————
PTQDModel=LDM-4, Steps=50, W/A=8/82025.0510.3154.1515.89—56.57
LDM-4Bops=98.36T, Speed=1.00x, Size=1317.4, Retrain=false, T=100, eta=02025.0310.49————
EDA-DMPrec. (W/A)=6/6, Architecture=LDM-4, Steps=100, eta=12025.0510.56——2.12—
Lite-LDM#Param=22.4M, MACs=7.9G2022.1110.9————
PTQDModel=LDM-4, Steps=50, W/A=4/82025.0510.9652.815.42—47.83
DeepcacheCache Frequency (N)=2, Bops=52.23T, Speed=1.79x, Compression Ratio=1.00x, Retrain=false, T=100, eta=02025.0311.21————
DeepcacheCache Frequency (N)=3, Bops=37.49T, Speed=2.68x, Compression Ratio=1.00x, Retrain=false, T=100, eta=02025.0311.86————
TALORAPrec. (W/A)=4/4, h=2, Architecture=LDM-4, Steps=100, eta=12025.0512.21——2.47—
TALORAPrec. (W/A)=4/4, h=4, Architecture=LDM-4, Steps=100, eta=12025.0512.34——2.48—
HQ-DMBit (W/A)=8/4, Model architecture=LDM-4, Denoising steps=1002025.1212.3537.4416.27—47.31
EfficientDMPrec. (W/A)=6/6, Architecture=LDM-4, Steps=100, eta=12025.0512.95——2.57—
HQ-DMBit (W/A)=4/4, Model architecture=LDM-4, Denoising steps=1002025.1213.1536.3417.53—45.32
DeepcacheCache Frequency (N)=5, Bops=24.59T, Speed=4.08x, Compression Ratio=1.00x, Retrain=false, T=100, eta=02025.0314.28————
SA-QLoRAModel=LDM-4, Steps=50, W/A=4/42025.0514.7245.618.19—41.84
EfficientDMBit (W/A)=4/4, Model architecture=LDM-4, Denoising steps=1002025.1216.8129.6620.81—41.42
EfficientDMBit (W/A)=8/4, Model architecture=LDM-4, Denoising steps=1002025.1217.9137.8619.44—40.4
HQ-DMBit (W/A)=3/4, Model architecture=LDM-4, Denoising steps=1002025.1219.2231.9219.29—38.32
EfficientDMModel=LDM-4, Steps=50, W/A=4/42025.0519.340.0922.63—43.77
EfficientDMBit (W/A)=3/4, Model architecture=LDM-4, Denoising steps=1002025.1220.9229.3822.78—38.57
HQ-DMBit (W/A)=4/3, Model architecture=LDM-4, Denoising steps=1002025.1221.8829.122.15—34.52
TFMQ-DMBit (W/A)=3/4, Model architecture=LDM-4, Denoising steps=1002025.1225.74—35.18—32.2
TFMQ-DMBit (W/A)=2/4, Model architecture=LDM-4, Denoising steps=1002025.1225.77—36.74——
EfficientDMBit (W/A)=4/3, Model architecture=LDM-4, Denoising steps=1002025.1226.829.0224.01—33.43
HQ-DMBit (W/A)=2/4, Model architecture=LDM-4, Denoising steps=1002025.1228.518.7630.17—32.64
EfficientDMBit (W/A)=2/4, Model architecture=LDM-4, Denoising steps=1002025.1233.6820.3427.19—28.76
EfficientDMPrec. (W/A)=4/4, Architecture=LDM-4, Steps=100, eta=12025.0536.36——2.69—