Simulating realistic Agentic workflow parameters (40,000 in / 1,500 out with 65% cache reuse). Kimi K3 (Moonshot) delivers a 44% cost reduction over GPT-5.6 Sol.
| Traffic Volume Tier | GPT-5.6 Sol Monthly | Kimi K3 (Moonshot) Monthly | Monthly Savings by picking Kimi K3 (Moonshot) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $128.00 | $72.30 | Save $55.70 / mo |
| 10,000 reqs/mo (Small App) | $1,280.00 | $723.00 | Save $557.00 / mo |
| 100,000 reqs/mo (Growth Production) | $12,800.00 | $7,230.00 | Save $5,570.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $128,000.00 | $72,300.00 | Save $55,700.00 / mo |
Kimi K3 (Moonshot) is 44% cheaper for Agentic workflow workloads. At standard Agentic workflow parameter ratios (40,000 input tokens, 1,500 output tokens, 65% cache hit), Kimi K3 (Moonshot) costs $0.0723 per request compared to $0.128 on GPT-5.6 Sol.
GPT-5.6 Sol offers a context window of 1,050,000 tokens (max output: 128,000), while Kimi K3 (Moonshot) offers 1,000,000 tokens (max output: 64,000).
At 100,000 requests per month, using Kimi K3 (Moonshot) saves $5,570.00 every month (or $66,840.00 annually) compared to GPT-5.6 Sol.
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.