Simulating realistic Agentic workflow parameters (40,000 in / 1,500 out with 65% cache reuse). GLM 4.7 (Zhipu) delivers a 55% cost reduction over Perplexity Sonar Reasoning Pro.
| Traffic Volume Tier | Perplexity Sonar Reasoning Pro Monthly | GLM 4.7 (Zhipu) Monthly | Monthly Savings by picking GLM 4.7 (Zhipu) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $92.00 | $41.475 | Save $50.525 / mo |
| 10,000 reqs/mo (Small App) | $920.00 | $414.75 | Save $505.25 / mo |
| 100,000 reqs/mo (Growth Production) | $9,200.00 | $4,147.50 | Save $5,052.50 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $92,000.00 | $41,475.00 | Save $50,525.00 / mo |
GLM 4.7 (Zhipu) is 55% cheaper for Agentic workflow workloads. At standard Agentic workflow parameter ratios (40,000 input tokens, 1,500 output tokens, 65% cache hit), GLM 4.7 (Zhipu) costs $0.0415 per request compared to $0.092 on Perplexity Sonar Reasoning Pro.
Perplexity Sonar Reasoning Pro offers a context window of 127,072 tokens (max output: 8,192), while GLM 4.7 (Zhipu) offers 128,000 tokens (max output: 16,384).
At 100,000 requests per month, using GLM 4.7 (Zhipu) saves $5,052.50 every month (or $60,630.00 annually) compared to Perplexity Sonar Reasoning Pro.
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.