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llm-cost-optimization

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Reduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and self-hosting strategies. Track spend by team and model, set budgets, and implement cost-aware routing.

When to use

• LLM API spend is growing faster than revenue
• You need to attribute AI costs to teams, products, or customers
• Implementing caching to avoid redundant LLM calls
• Deciding when to switch from API providers to self-hosted models
• Optimizing prompt length without sacrificing quality

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