CNNs and LLMs are fundamentally different architectures. LLMs do not operate on images directly. They need to be transformed into something that can ultimately be fed in as tokens. The ability to produce a confidence figure isn't possible until we've reached the end of the pipeline and the vision encoder has already done its job.
The images get converted to tokens using the vision encoder, But the tokens are just embedding vectors. So it should be able to if you train it.
CNNs and LLMs are not that different. You can train an LLM architecture to do the same thing that CNNs do with a few modifications, see Vision Transformers.