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Models/Fluid (10.5B)

Fluid (10.5B)

Reported on 28 benchmarks across 4 tasks · 1 paper · 28 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Audio14 results

10-shot image generationonGenEval
Color Attri.· 2024-10-17
0.51
best: 0.71 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
10-shot image generationonGenEval
Colors· 2024-10-17
0.8
best: 0.9 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
10-shot image generationonGenEval
Counting· 2024-10-17
0.63
best: 0.81 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
10-shot image generationonGenEval
Overall· 2024-10-17
0.69
best: 0.95 (SD3.5-Medium+Flow-GRPO)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
10-shot image generationonGenEval
Position· 2024-10-17
0.39
best: 0.74 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
10-shot image generationonGenEval
Single Obj.· 2024-10-17
0.96
best: 0.99 (MindOmni)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
10-shot image generationonGenEval
Two Obj.· 2024-10-17
0.83
best: 0.94 (MindOmni)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
1 Image, 2*2 StitchionGenEval
Color Attri.· 2024-10-17
0.51
best: 0.71 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
1 Image, 2*2 StitchionGenEval
Colors· 2024-10-17
0.8
best: 0.9 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
1 Image, 2*2 StitchionGenEval
Counting· 2024-10-17
0.63
best: 0.81 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
1 Image, 2*2 StitchionGenEval
Overall· 2024-10-17
0.69
best: 0.95 (SD3.5-Medium+Flow-GRPO)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
1 Image, 2*2 StitchionGenEval
Position· 2024-10-17
0.39
best: 0.74 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
1 Image, 2*2 StitchionGenEval
Single Obj.· 2024-10-17
0.96
best: 0.99 (MindOmni)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
1 Image, 2*2 StitchionGenEval
Two Obj.· 2024-10-17
0.83
best: 0.94 (MindOmni)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863

Medical7 results

Image GenerationonGenEval
Color Attri.· 2024-10-17
0.51
best: 0.71 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Image GenerationonGenEval
Colors· 2024-10-17
0.8
best: 0.9 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Image GenerationonGenEval
Counting· 2024-10-17
0.63
best: 0.81 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Image GenerationonGenEval
Overall· 2024-10-17
0.69
best: 0.95 (SD3.5-Medium+Flow-GRPO)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Image GenerationonGenEval
Position· 2024-10-17
0.39
best: 0.74 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Image GenerationonGenEval
Single Obj.· 2024-10-17
0.96
best: 0.99 (MindOmni)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Image GenerationonGenEval
Two Obj.· 2024-10-17
0.83
best: 0.94 (MindOmni)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863

Natural Language Processing7 results

Text-to-Image GenerationonGenEval
Color Attri.· 2024-10-17
0.51
best: 0.71 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Text-to-Image GenerationonGenEval
Colors· 2024-10-17
0.8
best: 0.9 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Text-to-Image GenerationonGenEval
Counting· 2024-10-17
0.63
best: 0.81 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Text-to-Image GenerationonGenEval
Overall· 2024-10-17
0.69
best: 0.95 (SD3.5-Medium+Flow-GRPO)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Text-to-Image GenerationonGenEval
Position· 2024-10-17
0.39
best: 0.74 (UniWorld-V1 (Rewrite))
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Text-to-Image GenerationonGenEval
Single Obj.· 2024-10-17
0.96
best: 0.99 (MindOmni)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863
Text-to-Image GenerationonGenEval
Two Obj.· 2024-10-17
0.83
best: 0.94 (MindOmni)
SOTA
Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens arXiv:2410.13863