Text-to-motion generation on HumanML3D 1 (test) benchmark leaderboard · SOTA2 Research

Text-to-motion generation on HumanML3D 1 (test)

0.517R-Precision (Top 1)TCA-T2M

Evaluation Results

Method	Links
TCA-T2M2026.02		0.517	0.709	0.806	0.068	2.951	9.485	1.103
MG-MotionLLM2026.02		0.516	0.706	0.802	0.303	2.952	9.96	2.125
PGR2M Recons.2025.12		0.514	0.702	0.796	0.007	2.968	9.555	—
Real Motion2025.12		0.511	0.703	0.797	0.002	2.974	9.503	—
Real2026.02		0.511	0.703	0.797	0.002	2.974	9.503	—
Light-T2M2026.02		0.511	0.699	0.795	0.04	3.002	—	1.67
GenM32026.02		0.511	0.705	0.804	0.046	2.852	9.675	—
CoMo Recons.2025.12		0.508	0.697	0.792	0.041	3.003	9.563	—
Momask2026.02		0.508	0.701	0.797	0.103	3.024	9.428	1.308
GraphMotion2025.12		0.504	0.699	0.785	0.116	3.07	9.692	2.766
FineMoGen2025.12		0.504	0.69	0.784	0.151	2.998	9.263	2.696
MMM2026.02		0.504	0.696	0.794	0.08	2.998	9.411	1.164
CoMo2025.12		0.502	0.692	0.79	0.262	3.032	9.936	1.013
MotionLCM2026.02		0.502	0.698	0.798	0.304	3.012	9.607	2.259
Mo.Mamba2026.02		0.502	0.693	0.792	0.281	3.06	9.871	2.294
CoMo2026.02		0.502	0.692	0.79	0.262	3.032	9.936	1.013
MotionGPT2025.12		0.492	0.681	0.778	0.232	3.096	9.528	2.008
T2M-GPT2026.02		0.492	0.679	0.775	0.141	3.121	9.722	1.831
MotionGPT2026.02		0.492	0.681	0.778	0.232	3.096	9.528	2.008
T2M-GPT2025.12		0.491	0.68	0.775	0.116	3.118	9.761	1.831
Mo.Diffuse2026.02		0.491	0.681	0.775	0.63	3.113	9.41	1.553
PGR2M (Base)2025.12		0.489	0.681	0.779	0.308	3.07	9.904	0.98
PGR2M2025.12		0.488	0.677	0.775	0.172	3.07	9.588	1.17
MLD2025.12		0.481	0.673	0.772	0.473	3.196	9.724	1.533
MLD2026.02		0.481	0.673	0.772	0.473	3.196	9.724	2.413
Guo et al.2025.12		0.457	0.639	0.74	1.067	3.34	9.188	2.09
T2M2026.02		0.455	0.636	0.736	1.087	3.347	9.175	2.219
TM2T2025.12		0.424	0.618	0.729	1.501	3.467	8.589	2.424
TM2T2026.02		0.424	0.618	0.729	1.501	3.467	9.92	2.424
MotionGPT2026.02		0.364	0.533	0.629	0.805	3.914	9.972	2.473
MDM2025.12		0.32	0.498	0.611	0.544	5.566	9.559	2.799
MDM2026.02		0.32	0.498	0.611	0.544	5.566	9.559	2.799