What does "Model context is full" mean?
The "Model context is full" message appears when your conversation has exceeded the AI model's context window—the maximum amount of information it can process at once.
Think of context as the model's "working memory." Every message you send, every response it generates, and all the information from your assistant's rules, datasources, and actions consume space in this context window. When that space fills up, the model can't accept any more information.
Why context limits exist
AI models have context limits for technical and practical reasons:
Processing constraints: Larger contexts require exponentially more computational power and memory
Response quality: Models perform best when working with focused, relevant information
Cost efficiency: Processing larger contexts costs more in terms of both time and money
Different models have different context limits. For example:
Smaller, faster models might have 8,000-16,000 token limits
Mid-range models typically offer 32,000-128,000 tokens
Advanced models can handle 200,000+ tokens
What fills up the context
Several factors contribute to context usage:
Conversation history: Every message in your conversation (both yours and the assistant's responses) takes up space
Assistant configuration:
Rules and instructions you've written
Context field information
Connected datasources that get retrieved
Enabled actions and their descriptions
Attachments: Files you've uploaded to the conversation
Integration data: Information pulled from connected tools and databases
Long conversations with extensive back-and-forth, large datasources, or many attached files will fill the context faster.
What to do when context is full
When you encounter this message, you have several options:
Start a new conversation
The simplest solution is to start a fresh conversation. This clears the context and gives you a clean slate.
When to start new:
You're switching to a completely different topic
The current conversation has served its purpose
You need to reset the assistant's "memory" of previous exchanges
Switch to a model with a larger context window
If you frequently hit context limits, consider using a model with a larger context window.
Go to your assistant's settings and select a model with higher context capacity. See How to choose the right LLM for your assistant for guidance on selecting appropriate models.
Optimize your assistant configuration
Review your assistant's setup to reduce unnecessary context usage:
Streamline your rules: Keep instructions concise and focused on behavior rather than facts. See 10 recommendations for writing assistant rules in elvex
Use datasources efficiently: Only connect datasources that are essential for your assistant's purpose. Remove any that aren't actively being used
Minimize the context field: Move factual information from the context field to datasources where possible. See Knowledge for your AI: Assistant instructions vs data sources
Disable unused actions: Turn off any actions your assistant doesn't need, as each enabled action adds to the context
Be strategic about conversation length
For tasks requiring extended back-and-forth:
Break complex projects into multiple focused conversations
Summarize key points before starting a new conversation
Reference specific information explicitly rather than relying on the model to remember everything
Related articles
Conversations - Learn when to start new conversations vs. continuing old ones
How to choose the right LLM for your assistant - Select models with appropriate context windows
10 recommendations for writing assistant rules in elvex - Optimize your assistant configuration
Knowledge for your AI: Assistant instructions vs data sources - Use context efficiently
Prompt caching in elvex - Understand how caching improves efficiency
