AI Token Cost Calculator
Calculate the cost of using AI language models based on token usage, request volume, and model pricing.
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* সব হিসাব আনুমানিক।
গুরুত্বপূর্ণ — সিদ্ধান্ত নেওয়ার আগে পড়ুন
- Output tokens typically cost 3–5x more than input tokens across most AI model providers.
- Prompt caching can reduce input token costs by up to 90% for repeated context and system prompts.
- Batch API processing is often 50% cheaper than real-time requests for non-urgent workloads.
- Token count varies by language — non-English languages generally consume more tokens per word.
- Model choice dramatically affects cost — smaller models can be 10–100x cheaper for simple tasks.
- Streaming responses does not change the pricing — you pay the same whether streaming or not.
- Context window size affects the maximum tokens per request and can impact per-request cost.
- Fine-tuned models have different pricing structures compared to base models and may cost more per token.
এগুলো উপেক্ষা করলে কী হবে?
- Not monitoring token usage leads to budget overruns that can accumulate quickly at scale.
- Verbose or poorly optimized prompts waste input tokens on every single request.
- Not implementing caching for repeated contexts multiplies costs unnecessarily across requests.
- Choosing the wrong model tier wastes money — using a premium model for simple tasks is inefficient.
- Operating without rate limiting or budget caps can cause runaway costs from bugs or traffic spikes.
স্মার্ট টিপস
- Use smaller, cheaper models for simple classification and extraction tasks that don't need advanced reasoning.
- Implement prompt caching for system prompts and repeated context to dramatically reduce input costs.
- Batch requests when real-time responses aren't needed to take advantage of lower batch pricing.
- Optimize prompts to be concise and specific, reducing unnecessary input tokens without losing quality.
- Set usage alerts and hard rate limits to prevent unexpected cost spikes from runaway usage.
- Consider open-source models for high-volume, simple tasks where API costs would be prohibitive.
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