● Covered by 1 source · 1 reportLow impact1 neutral
Tips for optimizing token usage in Claude Code sessions
Key points
- Clear context between tasks to reduce token usage.
- Use '/context' to review loaded information and remove unnecessary data.
- Utilize '/compact' before breaks to summarize conversations while cached.
- Token cost depends on model, input/output type, and caching.
Understanding Token Efficiency in AI Coding
Agentic coding tools like Claude Code incur costs per token, making efficient usage important. The same task can have varying token costs depending on how the session is managed. Efficiency means ensuring tokens contribute directly to the requested task, rather than processing irrelevant information.
Factors Influencing Token Cost
Token billing is based on the inference time required for a GPU to process tokens. Three main factors determine a token's cost: the specific model being used, whether it's an input or output token, and if it has been cached. Larger models generally perform more work on both input and output tokens, affecting the overall price.
Practical Strategies for Session Optimization
To maximize value, users should clear context with '/clear' between tasks to prevent irrelevant information from being sent to the model, reducing token usage. The '/context' command allows users to review loaded information and remove unnecessary data. Additionally, using '/compact' before taking a break is recommended, as the prompt cache expires after an hour, and summarizing a conversation is more cost-effective while it's still cached.
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Reporting from
This guide provides strategies for efficient token usage in Claude Code sessions to manage costs and improve model performance. It explains how token billing works and offers practical advice on managing context and session state.