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 Multi-Agent Orchestration 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 3,000 requests/day (540.0M monthly input tokens and 108.0M monthly output tokens with a 65% cache hit rate), GPT-4o costs $1991.25/month whereas Llama 3.1 405B costs $1275.75/monthโa monthly variance of $715.50 ($8586/year).
Frequently Asked Questions
Is GPT-4o or Llama 3.1 405B cheaper for Multi-Agent Orchestration?
Under standard Multi-Agent Orchestration parameters (3,000 reqs/day, 6000 input tokens, 1200 output tokens, 65% cache hit), Llama 3.1 405B is more cost-effective, saving $715.50 per month ($8586.00 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 Multi-Agent Orchestration 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.