Claude Opus 4.5 supports a 200K-token context window, but for production workloads developers are encouraged to use smaller, focused contexts—often 20K–80K tokens per request—except for occasional large tasks. Although the full 200K is available, running at the upper limit repeatedly can increase latency and reduce the clarity of model outputs. Keeping prompts concise and well-structured helps maintain consistent performance while staying comfortably within the available window.
In day-to-day use, many systems apply conversation-trimming rules, such as keeping only the last few interactions in full detail, while summarizing or removing older sections. This keeps the prompt small and easier for the model to reason over. A clean system prompt and consistent formatting also help Claude Opus 4.5 maintain stable behavior across requests, especially when building multi-turn assistants or programming tools.
When you need access to large source files, long documentation, or multi-file code references, a retrieval step is usually a better approach than placing everything into the prompt. A vector database such as Milvus or Zilliz Cloud can store embeddings of your documents or repository, and your application can retrieve only the most relevant chunks for each question. This keeps effective context sizes small while still giving Claude Opus 4.5 the information it needs to produce accurate results. For long-running agents, storing history outside the prompt and injecting only summaries helps maintain both performance and cost efficiency.