Is MuJoCo-cpu good enough for RL grasping and sim-to-real?

Hello guys, i have a question regarding simulator for RL training. My project focuses on training a 2-finger gripper to grasp a wide variety of objects with different shapes, sizes, and physical properties without sensors. Currently, im intentionally planning to use Mujoco (CPU-based, single environment training rather than parallel environments as isaaclab or mujocolab because the only gpu i have is gtx 2080-ti, and 16gb ram) to train the policy. I intend to adopt a heterogeneous training setup, where different target objects are changed across episodes, and i will use PPO as the learning algorithm. During training, i place particular emphasis on modeling physical properties such as contact forces, object weight, and interaction dynamics.

I also plan to deploy this policy on a real robot (UR3e + susgrip-2f gripper). I have previously worked with PyBullet for 4 montths, so sim-to-real transfer is also an important consideration in my setup.

My main question is: would Mujoco-cpu be sufficient for this type of task, particularly in terms of accurately simulating contact forces and enabling generalization across diverse objects, so that I can determine an effective plan for completing this project? please help mee