A mediocre fit (at best), X2/df and RMSEA are acceptable, the rest of your fit indices are at the threshold or below the threshold for acceptable fits. Some of the thresholds you've stated seem to be a bit lenient too, TLI and CFI > .90 is usually acceptable fits, below usually indicates poor fit.
You should look into the specific paths/factor loadings, maybe there are some weird cross-loadings/poor loadings, removing them could improve the fits
The fit of this model is not very good. One important aspect to consider here is that the model appears to be quite large as indicated by the large number of degrees of freedom (df = 732). Model size affects model fit tests (chi-square) and fit indices derived from chi-square. See, for example:
Herzog, W., Boomsma, A., & Reinecke, S. (2007). The model-size effect on traditional and modified tests of covariance structures. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 361-390.
Moshagen, M. (2012). The model size effect in SEM: Inflated goodness-of-fit statistics are due to the size of the covariance matrix. Structural Equation Modeling: A Multidisciplinary Journal, 19(1), 86-98.
Shi, D., Lee, T., & Terry, R. A. (2018). Revisiting the model size effect in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 25(1), 21-40.
Yuan K. H., Tian Y., Yanagihara H. (2015). Empirical correction to the likelihood ratio statistic for structural equation modeling with many variables. Psychometrika, 80, 379-405.
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