GPT-4o vs Gemini 1.5 Pro API Cost & Architecture Guide
Selecting between GPT-4o (OpenAI) and Gemini 1.5 Pro (Google) for production RAG Pipeline workloads requires balancing token pricing, prompt caching discounts, context window capacity (128K vs 2M), and streaming throughput (110 vs 75 tok/s).
GPT-4o is priced at $2.50 per 1M input tokens ($1.250/1M with prompt caching) and $10.00 per 1M output tokens. By comparison, Gemini 1.5 Pro charges $1.25 per 1M input tokens ($0.310/1M cached) and $5.00 per 1M output tokens.
At 5,000 requests/day (675.0M monthly input tokens and 90.0M monthly output tokens with a 60% cache hit rate), GPT-4o costs $2081.25/month whereas Gemini 1.5 Pro costs $913.05/monthโa monthly variance of $1168.20 ($14018/year).
Frequently Asked Questions
Is GPT-4o or Gemini 1.5 Pro cheaper for RAG Pipeline?
Under standard RAG Pipeline parameters (5,000 reqs/day, 4500 input tokens, 600 output tokens, 60% cache hit), Gemini 1.5 Pro is more cost-effective, saving $1168.20 per month ($14018.40 annually).
How does prompt caching affect GPT-4o vs Gemini 1.5 Pro pricing?
GPT-4o reduces cached input costs to $1.25/1M tokens, while Gemini 1.5 Pro charges $0.31/1M cached input tokens. High system-prompt reuse in RAG Pipeline pipelines can cut total input token spend by 50%โ90%.
What are the context window and speed differences between GPT-4o and Gemini 1.5 Pro?
GPT-4o supports a 128K token context window at ~110 tokens/sec, while Gemini 1.5 Pro provides a 2M token context window at ~75 tokens/sec.