A recent report by Chroma confirms what many AI roleplayers have repeatedly stated: a large context size negatively impacts AI roleplay.
To enhance their roleplaying experience, users often use advanced LLM models like DeepSeek, Gemini, and Claude. These models are trained on a broader range of data, support larger context sizes, generate creative responses, and follow instructions effectively.
What Are LLMs, Context Size, and Tokens?
When you roleplay with AI, you’re interacting with a Large Language Model (LLM) that converts your input into tokens, analyzes the context, and predicts the next token one at a time. It doesn’t communicate like a human; it follows patterns learned from training to generate the most probable response.
Context size, or context window, is the total number of tokens the LLM stores and references when generating a response. Think of it as your AI’s memory; the context size determines how much your AI character can remember.
If you’re into AI roleplay, you’ll notice these terms used often. We’ve written an in-depth guide about Understanding Tokens and Context Size.
Large Context Size and AI Roleplay
You might think that using an advanced LLM model with a larger context size will enhance your AI roleplay experience. After all, it’s beneficial for your roleplay if the AI “remembers” more details about its character, the surrounding world, and your conversation, right?
However, it’s not that simple, and a recent report by Chroma confirms what many AI roleplayers have repeatedly stated: a large context size negatively impacts AI roleplay.
Context Rot: Chroma’s Technical Report and Research
In simple terms, Chroma’s report states that LLMs struggle to maintain performance as the context increases. As a conversation or input gets longer, the AI becomes less effective at focusing on and using information within its context window.
The AI doesn’t treat all information in its context window equally, and data from earlier in the context “rots.” This occurs even on simple tasks, indicating that the length of the context, not just the task’s difficulty, is the issue.
Large Language Models (LLMs) are typically presumed to process context uniformly—that is, the model should handle the 10,000th token just as reliably as the 100th. However, in practice, this assumption does not hold. We observe that model performance varies significantly as input length changes, even on simple tasks.
The report provides a detailed explanation of the problem, its causes, and solutions to address the issue. It covers the issue generally, but we’re specifically focusing on how this impacts AI roleplay.
Large Context Size Negatively Impacts AI Roleplay
In AI roleplay, consistency and memory are crucial for an immersive experience. You interact with a character in an established setting and develop a story with the AI. Context rot can ruin your experience.
Core Character Consistency
You start a roleplay with Elara, a stoic and pragmatic Knight who deeply distrusts nobles and royalty. She’s a battle-hardened veteran always ready to face the problems and challenges that come her way.
Also Read: DeepSeek’s Input Tokens Cache And AI Roleplay
At the start of your roleplay, Elara’s responses will be consistent with her character as the AI will pay attention to key character details. However, once the context rot sets in, she’ll become a shell of her former self.
The Elara you expect to be stoic would begin responding with emotional and philosophical prose. Or she might easily trust nobility and royalty. The AI would forget Elara’s core traits or not consider them relevant as the context window grows.
Plot and Setting Details
You set out with Elara into a dense, thick forest to deal with a group of ruthless bandits. It’s raining, and the mud sinks under your feet with each step because of your armor and weapon’s weight. You locate the bandits, and a fight breaks out.
The AI will remember the setting and objective, and the start of your fight with the bandits will draw you in. But once the context rot sets in, Elara might forget it’s raining, that the forest floor sinks with each step, making her movements harder. She could even forget you’re in a forest, conjuring stairs to climb or walls to lean on.
The AI wouldn’t consider the plot or setting details relevant after many messages that focus on the details of an ongoing battle, NPC actions, dialogues, etc.
Inconsistent AI Behavior
At the beginning of your roleplay, the AI will consistently remember minor details, small hints, or subplots. However, as the roleplay continues and the context rot sets in, it will start acting inconsistently.
The AI might start forgetting details like your character’s eye color or the weapon they carry. It could begin reading your thoughts or respond with information you haven’t explicitly shared with your AI character. The AI might even start controlling your actions and dialogues.
Context Rot Is A Problem For Roleplay
It’s a frustrating experience when a large context size negatively impacts AI roleplay due to context rot.
It disrupts the immersion when you constantly have to nudge the AI with OOC instructions or edit its responses. It becomes frustrating when you feel that the AI isn’t listening or remembering. And you lose interest in continuing the roleplay when the AI loses the plot.
We’ve all given up on an AI character at some point because managing it requires more effort than enjoying the story.
How To Avoid Context Rot
The first step is to avoid using a large context size. The ideal context window is between 8,192 and 16,384 tokens. It may be tempting to use a bigger context size, but focusing on optimizing other aspects of your roleplay and staying within the ideal context window will result in a better and more consistent roleplay experience.
Focused Prompts In Permanent Tokens
While creating your AI character, keep your prompts within the permanent tokens focused. Permanent tokens should include traits and information that define your character, and only consist of prompts that the LLM can use to shape your character.
For example, define Elara’s core traits within your permanent tokens. Stoic, battle-hardened, distrusts nobility, etc. Include prompts that describe her appearance, such as her deep blue eyes, carrying a sword with a golden pommel, and wearing a helmet shaped like a falcon, etc.
You don’t need to stick to using keywords or one-liners. Your prompts can flow naturally as sentences or paragraphs. However, make sure they are vital to defining your character.
Example Of A Focused Prompt
Elara’s past battles and the scars she bears have given her valuable experience and shaped her into one of the fiercest knights in the Kingdom of Leon. The stories of her fights and achievements have also earned her the respect and admiration of Leon’s citizens. Elara’s accomplished yet brutal past has made her a pragmatic and stoic person, holding firmly to the way of life that has kept her alive.
- Defines her as a battle-hardened veteran Knight.
- Provides her origin as a citizen of the Kingdom of Leon.
- Sets her up as a respected and admired character by the commoners.
- Defines her traits and connects them to her belief that she’s alive because of those traits.
This is an example of how you can include a focused prompt within the permanent tokens. Every character creator has their own approach to building prompts for their creations, and there’s no one-size-fits-all method.
Summarization and Chat Memory
Most AI roleplay platforms provide a Summarization or Chat Memory feature, which lets you create a summary of your conversation or manually add details and control what stays in the AI’s context window.
Using this feature effectively is the key to enjoying long roleplays that span hundreds of messages without requiring a large context size. Think of it as a summary of each chapter in a storybook, gradually building up to the finale.
Keep your summary or chat memory focused. Concise details that help not only the AI but also you remember key points of your roleplay easily.
Quality In, Quality Out
Be a good roleplay partner to your AI. Write detailed, quality messages that help the AI generate more engaging responses.
For example, instead of a simple message:
Wayfarer walked through the dense forest as it rained, using his sword to clear the path ahead as they went deeper in search of the bandits.
Use a more descriptive and immersive message:
As it started pouring heavily, Wayfarer found it harder to walk through the thick forest. The weight of his armor made his feet sink into the wet, muddy ground. But he kept moving forward, one slow step at a time, clearing the path ahead with his sword as they ventured deeper into the lush forest in search of the bandits.
The AI will follow your lead, using context clues from your response to craft its immersive reply.
Use Retrievable Information
If your platform supports features like lorebooks, databanks, or other tools that let your AI character access retrievable information, use them to give the AI extra details only when needed.
The AI will only retrieve information from within a lorebook when triggered by keywords. You can keep the prompts in your permanent tokens more focused, and move situational or specific prompts to a lorebook.
For example, the trigger word “Oathkeeper” can help the AI retrieve a lorebook entry describing the detailed appearance of the sword named Oathkeeper only when needed. The precious permanent tokens that this detail would have used are now available for other focused prompts to define your character.
Conclusion
It’s tempting to think that a larger context window automatically enhances roleplay, but as many experienced AI roleplayers have long argued, making it too big can do more harm than good.
What was once anecdotal advice is now supported by research, with Chroma’s report confirming that large context sizes negatively affect an LLM’s performance, causing the frustrating issue of context rot.
Ultimately, the key to a more immersive and consistent AI roleplay isn’t a massive context size but a smarter one. By staying within the ideal range of 8,192 to 16,384 tokens and using focused prompts, chat summaries, and lorebooks effectively, you can create a much more stable and engaging experience.
It’s about quality over quantity; giving the AI clear, concise, and relevant information will always outperform a sprawling context window that it struggles to remember.
