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Understanding "Model context is full"

This article explains what the "Model context is full" message means, why it happens, and what you can do about it.

Updated over 2 weeks ago

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

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