Simulating realistic Agentic workflow parameters (40,000 in / 1,500 out with 65% cache reuse). MiniMax-01 (4M Context) delivers a 87% cost reduction over GLM 4.7 (Zhipu).
| Traffic Volume Tier | GLM 4.7 (Zhipu) Monthly | MiniMax-01 (4M Context) Monthly | Monthly Savings by picking MiniMax-01 (4M Context) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $41.475 | $5.49 | Save $35.985 / mo |
| 10,000 reqs/mo (Small App) | $414.75 | $54.90 | Save $359.85 / mo |
| 100,000 reqs/mo (Growth Production) | $4,147.50 | $549.00 | Save $3,598.50 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $41,475.00 | $5,490.00 | Save $35,985.00 / mo |
MiniMax-01 (4M Context) is 87% cheaper for Agentic workflow workloads. At standard Agentic workflow parameter ratios (40,000 input tokens, 1,500 output tokens, 65% cache hit), MiniMax-01 (4M Context) costs $0.00549 per request compared to $0.0415 on GLM 4.7 (Zhipu).
GLM 4.7 (Zhipu) offers a context window of 128,000 tokens (max output: 16,384), while MiniMax-01 (4M Context) offers 4,000,000 tokens (max output: 64,000).
At 100,000 requests per month, using MiniMax-01 (4M Context) saves $3,598.50 every month (or $43,182.00 annually) compared to GLM 4.7 (Zhipu).
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.