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Every interaction with Claude Code consumes tokens -- the fundamental unit of measurement for large language model usage. Tokens represent chunks of text, where roughly 4 characters equal one token and 100 tokens approximate 75 English words. Understanding token consumption is critical for managing costs, optimizing workflows, and staying within plan limits.
Claude Code sessions involve two types of token consumption: input tokens and output tokens. Input tokens include everything sent to the model -- your prompts, system instructions, CLAUDE.md configuration, loaded file contents, and the accumulated conversation history. Output tokens cover Claude's responses, including generated code, explanations, tool call arguments, and reasoning traces. In a typical session, input tokens dominate at roughly 65% of total usage because the model must ingest your codebase context on every turn.
The ratio of input to output tokens shifts depending on your task. Code review sessions are heavily input-weighted because Claude reads many files but produces short assessments. Code generation sessions skew more toward output as Claude writes large blocks of new code. Debugging sits in between, with iterative cycles of reading error context and proposing fixes.
All current Claude models -- Haiku 4.5, Sonnet 4.6, and Opus 4.6 -- share a 200,000-token context window. This window acts as the model's working memory: it holds the entire conversation, system prompt, tool definitions, and any files loaded into context. Once the conversation approaches the window limit, Claude Code must either compact the conversation or start a fresh session.
Context window utilization directly impacts response quality. When the window is under 50% full, Claude has ample room to reason and produce detailed responses. Between 50-80%, you may notice slightly less thorough responses as the model manages its available space. Above 80%, response quality can degrade noticeably, and you risk hitting hard limits that force compaction. The /compact command summarizes conversation history into a condensed form, freeing context space without losing essential information.
Codebase size has a multiplicative effect on context usage. When Claude Code works with a 100K-line codebase, it may load 10-20% of the relevant files into context per turn. That means a single turn could consume 15,000-30,000 tokens just for file contents before any prompt or response tokens are counted. For large codebases, aggressive use of .claudeignore to exclude irrelevant directories is essential.
Effective token management can reduce your monthly usage by 40-60% without sacrificing productivity. Here are the most impactful strategies, ranked by effectiveness:
/compact after every 3 exchanges to reset context accumulation. This single habit has the largest impact on total token usage.node_modules, dist, .git, test fixtures, and other directories Claude does not need to read..claudeignore to exclude irrelevant directories./compact command summarizes your conversation history into a condensed form, dramatically reducing the token count carried forward. Using /compact after every 3 exchanges can reduce total session token usage by 40-60%. It preserves key decisions and context while removing verbose intermediate steps./compact frequently, choose Haiku for simple tasks, keep CLAUDE.md under 500 lines, avoid loading unnecessary files, and break large tasks into focused sessions. The Max plan offers unlimited tokens for heavy users who regularly exceed Pro limits.Related tools: Cost Calculator | Cost Optimization Guide | Configuration Guide
Pre-built configurations that cut token waste by 40-60%