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Text-to-Image Generation on DiffusionDB (test)

7.426Aesthetic ScoreOracle
2.989364.141185.2936.44482Jun 17, 2025

Evaluation results

MethodLinks
OracleModel=SDXL, TFLOPs=119.702025.067.426———————————————0.3340.1451.446
OracleModel=DEEP, TFLOPs=210.002025.067.421———————————————0.3370.1461.446
OracleModel=SDXL, TFLOPs=239.402025.067.416———————————————0.3370.1461.444
OracleModel=LIGH, TFLOPs=23.922025.067.385———————————————0.3230.1441.416
OracleModel=SDXL, TFLOPs=598.502025.067.284———————————————0.3360.1451.376
OracleModel=DDIM, TFLOPs=598.502025.067.284———————————————0.3360.1451.376
OracleModel=TURB, TFLOPs=1.542025.067.132———————————————0.3090.141.303
CATImageTarget Budget Reference=DDIM, TFLOPs=598.5, Fraction of TFLOPs=33.5%2025.067.109——————————————————
CATImageTarget Budget Reference=SDXL-50, TFLOPs=598.5, Fraction of TFLOPs=33.5%2025.067.109——————————————————
CATImageTarget Budget Reference=FLUX-15, TFLOPs=892.8, Fraction of TFLOPs=50.0%2025.067.108——————————————————
CATImageTarget Budget Reference=SDXL100, TFLOPs=1197.00, Fraction of TFLOPs=67.0%2025.067.09——————————————————
CATImageTarget Budget Reference=SDXL-20, TFLOPs=239.4, Fraction of TFLOPs=13.4%2025.067.087——————————————————
CATImageTarget Budget Reference=DeepCache, TFLOPs=210, Fraction of TFLOPs=11.8%2025.067.082——————————————————
CATImageTarget Budget Reference=SDXL-10, TFLOPs=119.70, Fraction of TFLOPs=6.7%2025.067.068——————————————————
CATImageTarget Budget Reference=FLUX-1, TFLOPs=59.52, Fraction of TFLOPs=3.3%2025.067.055——————————————————
CATImageTarget Budget Reference=Lighting, TFLOPs=23.92, Fraction of TFLOPs=1.3%2025.067.045——————————————————
CATImageModel=LIGH, TFLOPs=23.922025.067.042———————————————0.3080.1351.086
CATImageModel=SDXL, TFLOPs=119.702025.067.032———————————————0.3140.1361.086
CATImageModel=DEEP, TFLOPs=210.002025.067.012———————————————0.3160.1371.079
CATImageModel=SDXL, TFLOPs=239.402025.067.012———————————————0.3170.1371.076
Fixed BaselineTarget Budget Reference=Lighting, TFLOPs=23.92, Fraction of TFLOPs=1.3%2025.067.01——————————————————
FixedModel=LIGH, TFLOPs=23.922025.067.01———————————————0.30.110.932
CATImageTarget Budget Reference=FLUX-30, TFLOPs=1785.60, Fraction of TFLOPs=100.0%2025.066.983——————————————————
Fixed BaselineTarget Budget Reference=FLUX-30, TFLOPs=1785.60, Fraction of TFLOPs=100.0%2025.066.983——————————————————
Fixed BaselineTarget Budget Reference=FLUX-15, TFLOPs=892.8, Fraction of TFLOPs=50.0%2025.066.952——————————————————
CATImageModel=SDXL, TFLOPs=598.502025.066.935———————————————0.3180.1371.037
CATImageModel=DDIM, TFLOPs=598.502025.066.935———————————————0.3180.1371.037
CATImageTarget Budget Reference=Turbo, TFLOPs=1.54, Fraction of TFLOPs=0.1%2025.066.913——————————————————
CATImageModel=TURB, TFLOPs=1.542025.066.913———————————————0.3040.1351.083
CATImageTarget Budget Reference=Infinity, TFLOPs=1.50, Fraction of TFLOPs=0.1%2025.066.824——————————————————
Fixed BaselineTarget Budget Reference=Infinity, TFLOPs=1.50, Fraction of TFLOPs=0.1%2025.066.824——————————————————
OracleModel=INFI, TFLOPs=1.502025.066.824———————————————0.2590.1311.029
CATImageModel=INFI, TFLOPs=1.502025.066.824———————————————0.2590.1311.029
FixedModel=INFI, TFLOPs=1.502025.066.824———————————————0.2590.1311.029
Fixed BaselineTarget Budget Reference=Turbo, TFLOPs=1.54, Fraction of TFLOPs=0.1%2025.066.78——————————————————
FixedModel=TURB, TFLOPs=1.542025.066.78———————————————0.3040.1220.96
Fixed BaselineTarget Budget Reference=SDXL100, TFLOPs=1197.00, Fraction of TFLOPs=67.0%2025.066.707——————————————————
OracleModel=SDXL, TFLOPs=1197.002025.066.707———————————————0.3180.1260.891
CATImageModel=SDXL, TFLOPs=1197.002025.066.707———————————————0.3180.1260.891
FixedModel=SDXL, TFLOPs=1197.002025.066.707———————————————0.3180.1260.891
Fixed BaselineTarget Budget Reference=SDXL-50, TFLOPs=598.5, Fraction of TFLOPs=33.5%2025.066.69——————————————————
FixedModel=SDXL, TFLOPs=598.502025.066.69———————————————0.3170.1230.866
Fixed BaselineTarget Budget Reference=DeepCache, TFLOPs=210, Fraction of TFLOPs=11.8%2025.066.625——————————————————
FixedModel=DEEP, TFLOPs=210.002025.066.625———————————————0.3160.1010.809
Fixed BaselineTarget Budget Reference=DDIM, TFLOPs=598.5, Fraction of TFLOPs=33.5%2025.066.6——————————————————
FixedModel=DDIM, TFLOPs=598.502025.066.6———————————————0.3150.1070.861
Fixed BaselineTarget Budget Reference=SDXL-20, TFLOPs=239.4, Fraction of TFLOPs=13.4%2025.066.588——————————————————
FixedModel=SDXL, TFLOPs=239.402025.066.588———————————————0.3150.1140.769
Fixed BaselineTarget Budget Reference=SDXL-10, TFLOPs=119.70, Fraction of TFLOPs=6.7%2025.066.285——————————————————
FixedModel=SDXL, TFLOPs=119.702025.066.285———————————————0.3080.1030.497
Fixed BaselineTarget Budget Reference=FLUX-1, TFLOPs=59.52, Fraction of TFLOPs=3.3%2025.063.16——————————————————
AutoLoRAPre-trained Model=SD152026.03—35.6225.566.1520.1783.02—————————————
AutoLoRAPre-trained Model=FLUX2026.03—102.3329.756.1721.0179.85—————————————
DAREPre-trained Model=SD152026.03—28.0224.785.9519.7483.47—————————————
DAREPre-trained Model=FLUX2026.03—100.2128.876.1820.8779.79—————————————
DiffAgentPre-trained Model=SD152026.03—52.6527.526.3920.3184.84—————————————
DiffAgentPre-trained Model=FLUX2026.03—124.5130.266.2321.1881.36—————————————
Diffusion SoupPre-trained Model=SD152026.03—33.7925.646.0420.3984.61—————————————
Diffusion SoupPre-trained Model=FLUX2026.03—115.2430.036.121.2578.95—————————————
DirectPre-trained Model=SD152026.03—14.8323.745.8719.6182.7—————————————
DirectPre-trained Model=FLUX2026.03—91.1429.46.1320.6779.12—————————————
DPOBase Model=SD3-M, Alignment Method=DPO2026.05——————24.19324.20734.12633.8921.8311.6836.0876.07240.31240.288———
DPOBase Model=FLUX2026.05——————24.75124.74633.90133.7541.8051.6776.3116.31539.40539.374———
ESA*+K-LoRAPre-trained Model=SD15, Modified ESA module=true2026.03—27.1425.426.119.9485.16—————————————
ESA*+K-LoRAPre-trained Model=FLUX, Modified ESA module=true2026.03—110.9829.736.1420.9780.84—————————————
ESA*+LoRA.rarPre-trained Model=SD15, Modified ESA module=true2026.03—34.2325.466.1420.2485.41—————————————
ESA*+LoRA.rarPre-trained Model=FLUX, Modified ESA module=true2026.03—96.4528.516.1520.5979.42—————————————
FLUXBase Model=FLUX2026.05——————24.70124.70733.71633.4291.7871.6026.2866.27439.06739.243———
IPOBase Model=SD3-M, Alignment Method=IPO2026.05——————24.17224.18834.05833.8471.8291.6726.0716.06340.25140.229———
IPOBase Model=FLUX2026.05——————24.73924.72833.95333.7031.8031.6636.3486.36239.35139.366———
Model SwarmsPre-trained Model=SD152026.03—50.6226.635.9319.7182.94—————————————
Model SwarmsPre-trained Model=FLUX2026.03—120.8230.226.1721.2681.07—————————————
OursPre-trained Model=SD152026.03—85.429.486.6621.0585.86—————————————
OursPre-trained Model=FLUX2026.03—148.7532.366.6421.8482.66—————————————
Ours fixedPre-trained Model=SD152026.03—54.8327.676.220.4885.13—————————————
Ours fixedPre-trained Model=FLUX2026.03—123.1930.56.4521.5881.34—————————————
PNAPOBase Model=SD3-M, Alignment Method=PNAPO2026.05——————24.24624.25134.74834.2851.8381.7146.2126.16440.48940.481———
PNAPOBase Model=FLUX2026.05——————24.88324.89934.32734.341.8121.6996.4736.48239.68639.43———
SD3-MBase Model=SD3-M2026.05——————24.07624.07933.8533.4851.7841.5816.1456.13239.73739.714———
SFTBase Model=SD3-M, Alignment Method=SFT2026.05——————24.14124.16433.68633.3071.8241.646.0145.99840.140.104———
SFTBase Model=FLUX2026.05——————24.72324.72733.92933.6581.81.656.3396.3439.31639.369———