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Speed Up Claude Code and Cut API Latency

Why Claude Code Feels Slow

Claude Code latency usually comes from several small bottlenecks rather than one problem. A large project scan, an overloaded context window, a slow model, repeated tool calls, or network distance can each add seconds. The best improvement depends on which part of the workflow is actually slow, so begin by measuring the delay between your prompt, Claude's response, and each tool execution.

1. Keep the Working Context Focused

Claude Code is more responsive when it has fewer irrelevant files and instructions to process. Start sessions with a narrow task and identify the exact directories involved. Ask Claude to inspect specific files before asking for a broad repository review. Keep project guidance concise: a focused CLAUDE.md should explain build commands, testing conventions, architecture rules, and important constraints, but should not duplicate every README or generated file.

• Exclude build output, dependency folders, logs, caches, and large generated assets from routine inspection.
• Break a major refactor into small, testable units instead of requesting a whole-repository rewrite.
• Summarize completed work before moving to a new area so old context does not keep expanding.

2. Choose the Right Claude Model

Model selection has a direct effect on both response time and price. Use Haiku for quick explanations, straightforward edits, file lookups, and repetitive transformations. Sonnet is a strong default for implementation, debugging, and code review. Reserve Opus for difficult architectural decisions, subtle bugs, or work where deeper reasoning is worth the extra wait. A practical workflow is to prototype with Haiku or Sonnet, then send only the uncertain design question to Opus.

3. Reduce Unnecessary Tool Calls

Repeated searches and serial commands can make a simple task feel slow. Give Claude precise acceptance criteria and ask it to group safe read-only checks where possible. For example, requesting the relevant configuration files, test command, and current error in one investigation is usually more efficient than asking three separate questions. Keep shell commands targeted, and avoid repeatedly scanning the entire repository after every small edit.

4. Improve the API Path

Network overhead matters, especially when your workflow makes many short requests. Configure Claude Code with a reliable API endpoint close to your users or development environment, and check whether a proxy is adding retries or buffering. With 59API, you can use the API base URL https://api.59api.com while keeping compatibility with Claude Code, Codex, and OpenAI SDK-based tools. It provides pay-as-you-go access to Claude Opus, Sonnet, Haiku, and Fable, as well as GPT models, using native official-quality models rather than a downgraded substitute.

59API is also a useful option when API cost is limiting how often your team can run coding agents. Its low-cost relay model helps keep experimentation affordable, and its referral rebate can reduce effective spend for users who share the service. Latency still depends on your location, traffic, model, and prompt size, so compare a few representative tasks instead of judging an endpoint from one request.

5. Use Caching and Stable Instructions Carefully

If your integration supports prompt caching, keep stable project instructions and reusable schemas together, while placing changing task details afterward. This can reduce repeated processing for long system context. Avoid changing timestamps, random IDs, or duplicated status text in the stable portion, because unnecessary variation can prevent cache reuse. Also set practical token limits: a response that is allowed to produce thousands of lines will take longer than one constrained to a patch summary and tests.

Quick Claude Code Latency Checklist

• Measure prompt, model, network, and tool-execution time separately.
• Use Haiku for routine work, Sonnet for most coding, and Opus for hard reasoning.
• Keep CLAUDE.md and active file context short and relevant.
• Exclude generated files and dependencies from broad searches.
• Batch safe investigation steps and avoid redundant scans.
• Test the 59API endpoint with your real prompts before changing your production setup.

For developers who want affordable access while tuning a Claude Code workflow, signing up for 59API is a sensible low-risk experiment: start with pay-as-you-go usage, compare latency and output quality, and keep the model that fits each task.