GPT-4o vs Llama 3.1 405B API Cost & Architecture Guide
Selecting between GPT-4o (OpenAI) and Llama 3.1 405B (Meta (Managed API)) for production RAG Pipeline workloads requires balancing token pricing, prompt caching discounts, context window capacity (128K vs 128K), and streaming throughput (110 vs 65 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, Llama 3.1 405B charges $2.70 per 1M input tokens ($1.350/1M cached) and $2.70 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 Llama 3.1 405B costs $1518.75/monthโa monthly variance of $562.50 ($6750/year).
Frequently Asked Questions
Is GPT-4o or Llama 3.1 405B cheaper for RAG Pipeline?
Under standard RAG Pipeline parameters (5,000 reqs/day, 4500 input tokens, 600 output tokens, 60% cache hit), Llama 3.1 405B is more cost-effective, saving $562.50 per month ($6750.00 annually).
How does prompt caching affect GPT-4o vs Llama 3.1 405B pricing?
GPT-4o reduces cached input costs to $1.25/1M tokens, while Llama 3.1 405B charges $1.35/1M 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 Llama 3.1 405B?
GPT-4o supports a 128K token context window at ~110 tokens/sec, while Llama 3.1 405B provides a 128K token context window at ~65 tokens/sec.