Question 1

Which LLM is cheapest for production use?

Accepted Answer

For high-volume workloads: Llama 3.1 70B via Groq (~$0.59/M tokens) and Gemini 1.5 Flash (~$0.075/M tokens) are the most economical. For quality-sensitive production: Claude 3.5 Haiku and GPT-4o Mini offer the best cost-quality balance at $0.80-1.00/M tokens. GPT-4o and Claude 3.5 Sonnet are 10-15x more expensive but better for complex reasoning.

Question 2

How do input vs output token costs differ?

Accepted Answer

Output tokens typically cost 3-4x more than input tokens. GPT-4o: $2.50/M input, $10/M output. Claude 3.5 Sonnet: $3/M input, $15/M output. This means chatbots and long-form generation are proportionally more expensive than classification tasks that require short outputs.

Question 3

Should I switch LLM providers to save money?

Accepted Answer

Run a quality benchmark first. For tasks where any capable LLM works (classification, extraction, simple Q&A), switching to a cheaper model can cut costs 80-90%. For nuanced reasoning, instruction-following, and code generation, the quality difference matters more. A/B test with 5% of traffic before committing.

Question 4

What hidden costs should I budget for?

Accepted Answer

Beyond token costs: (1) Context caching — long system prompts repeated on every call; (2) Rate limit overages — paying for burst capacity; (3) Embeddings for RAG pipelines (separate pricing); (4) Input preprocessing (tokenization, chunking compute); (5) Retry costs from model errors (typically 0.1-1% of requests). Budget 20-30% above raw token costs.

LLM Cost Comparison Calculator — GPT-4o vs Claude vs Gemini 2025

Frequently Asked Questions

From the Blog