How well do GLM 5 and DeepSeek V3.2 handle character prompts of around 4,800 tokens on CaveDuck?

I am a Korean CaveDuck creator, and I am using a translator for this post. I recently noticed that many of the non-Korean users chatting with my characters choose GLM 5 or DeepSeek V3.2 rather than the models I normally use for testing.

Most of my character prompts are written in YAML. After trying to remove repetition and optimize the wording, they usually end up at around 4,000–5,000 tokens, with approximately 4,800 being fairly common.

CaveDuck’s character creation page currently describes prompt lengths roughly like this:

* 0–4,000 tokens: Comfortable

* 4,000–6,000 tokens: Moderate

* 6,000–8,000 tokens: High

* 8,000+: Over the recommended limit

The official CaveDuck guide also recommends keeping the total prompt length at around 2,000 tokens when using cheaper models.

My main questions are:

1. Can GLM 5 and DeepSeek V3.2 reliably handle a character prompt of around 4,800 tokens on CaveDuck?

2. Is it nearly impossible to determine a generally appropriate prompt length for each model, meaning that creators ultimately have no reliable option other than testing it themselves?

3. What are the strengths and weaknesses of GLM 5 and DeepSeek V3.2 specifically for character roleplay?

4. Are there particular genres, character types, or scenes that either model handles especially well or poorly?

Reviews in Korean CaveDuck communities tend to focus heavily on Gemini and Claude Opus models, so I have found much less detailed information about GLM 5 and DeepSeek V3.2. However, my character statistics suggest that a noticeable number of international users prefer these cheaper models.

I would therefore especially appreciate answers from people who have used either model extensively on CaveDuck. I am less interested in general benchmark performance and more interested in actual character-chat behavior: memory, instruction-following, dialogue quality, prose style, pacing, emotional nuance, repetition, and long-term consistency.

I would like non-Korean users to have a good experience with my characters as well, so I am trying to determine whether I should optimize the prompts further or provide a note recommending certain models.