Is it correct to compare score of different estimators?
If you have a similar pipeline to feed the same data into the models, then the metrics are comparable. You can choose the SVR Model without any doubt.
By the way, it could be really interesting for you to "redevelop" this "R_squared" Metric, it could be a nice way to learn the underlying mechanic.
I am getting different score values from different estimators from scikit.

SVR(kernel='rbf', C=1e5, gamma=0.1) 0.97368549023058548
Linear regression 0.80539997869990632
DecisionTreeRegressor(max_depth = 5) 0.83165426563946387

Since all regression estimators should use R-square score, I think they are comparable, i.e. the closer the score is to 1, the better the model is trained. However, each model implements score function separately so I am not sure. Please clarify.