[D] How does `@jax.jit` compare with PyTorch's `@torch.compile`?

Have any of you seen benchmarks comparing the performance of \`@jax.jit\` and \`@torch.compile\`, especially when using functional PyTorch code? Are the performance differences big? Small? Do they depend a lot on what you're doing?

benchmarks big code differences functional jax jit machinelearning performance pytorch small torch