Simulating realistic Agentic workflow parameters (40,000 in / 1,500 out with 65% cache reuse). DeepSeek Coder V2.5 delivers a 96% cost reduction over Llama 3.1 405B Instruct.
| Traffic Volume Tier | DeepSeek Coder V2.5 Monthly | Llama 3.1 405B Instruct Monthly | Monthly Savings by picking DeepSeek Coder V2.5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $2.744 | $75.25 | Save $72.506 / mo |
| 10,000 reqs/mo (Small App) | $27.44 | $752.50 | Save $725.06 / mo |
| 100,000 reqs/mo (Growth Production) | $274.40 | $7,525.00 | Save $7,250.60 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $2,744.00 | $75,250.00 | Save $72,506.00 / mo |
DeepSeek Coder V2.5 is 96% cheaper for Agentic workflow workloads. At standard Agentic workflow parameter ratios (40,000 input tokens, 1,500 output tokens, 65% cache hit), DeepSeek Coder V2.5 costs $0.002744 per request compared to $0.0753 on Llama 3.1 405B Instruct.
DeepSeek Coder V2.5 offers a context window of 128,000 tokens (max output: 8,192), while Llama 3.1 405B Instruct offers 128,000 tokens (max output: 4,096).
At 100,000 requests per month, using DeepSeek Coder V2.5 saves $7,250.60 every month (or $87,007.20 annually) compared to Llama 3.1 405B Instruct.
Prompt caching is the single biggest lever — each step re-reads prior context. Summarize or prune tool outputs before appending them to the transcript. Cap the step budget; runaway loops are the #1 surprise on agent invoices.