If you actively use AI assistants for programming, you've probably noticed how quickly tokens get consumed. This is especially true when working with tools like Claude Code or Codex. But don't rush to overpay — there are several proven ways to cut costs without losing efficiency.
Why Tokens Cost Money
AI models process text by tokens — fragments of words. The more context you send, the more tokens are used. And if you're on paid subscriptions or APIs, every extra token hits your budget. This is particularly relevant for developers working with large codebases.
12 Ways to Reduce Costs
Optimize context. Don't send the whole file if you only need a snippet. Highlight specific functions or classes.
Use constrained prompts. Clearly formulate the task, specify what not to consider. For example: "Don't analyze tests, only the main code."
Choose the model for the task. For simple tasks, you don't need a top-tier model — a cheaper one will do. Save on complex requests.
Cache results. If you frequently request the same thing, save the answers to avoid spending tokens repeatedly.
Work with diffs, not whole files. Send only changes, not the entire code, so the model sees relevant context.
Use local models. For routine tasks, local models like Llama are free and don't consume tokens.
Break down large tasks. Instead of one huge request, make several small ones — less chance the model gets confused and you have to re-ask.
Tune generation parameters. Limiting response length, temperature — all affect token usage.
Use tools wisely. Some IDEs and plugins allow configuring auto-completion to avoid generating unnecessary code.
Monitor statistics. Track which requests are most expensive and optimize them.
Use streaming. If the model supports streaming, you can stop the response as soon as you get what you need.
Plan ahead. Before starting, think about what exactly you want from the AI to avoid unnecessary iterations.
What This Means in Practice
Knowing how to save tokens is not just about money. It's also about speed: fewer tokens — faster responses. And if you pay for AI services with a virtual card, controlling expenses becomes especially important — you always know how much you spend.
Try implementing at least a few of these methods, and you'll notice a difference in your AI tool bills. And if you're looking for ways to pay for foreign AI services, virtual cards can be a convenient solution.
This material is for informational purposes and does not constitute financial advice.
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