Simulating realistic Customer support chatbot parameters (3,500 in / 350 out with 70% cache reuse). o3-mini delivers a 34% cost reduction over GLM 5.2 (Zhipu).
| Traffic Volume Tier | o3-mini Monthly | GLM 5.2 (Zhipu) Monthly | Monthly Savings by picking o3-mini |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $4.043 | $6.09 | Save $2.047 / mo |
| 10,000 reqs/mo (Small App) | $40.425 | $60.90 | Save $20.475 / mo |
| 100,000 reqs/mo (Growth Production) | $404.25 | $609.00 | Save $204.75 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $4,042.50 | $6,090.00 | Save $2,047.50 / mo |
o3-mini is 34% cheaper for Customer support chatbot workloads. At standard Customer support chatbot parameter ratios (3,500 input tokens, 350 output tokens, 70% cache hit), o3-mini costs $0.004043 per request compared to $0.00609 on GLM 5.2 (Zhipu).
o3-mini offers a context window of 200,000 tokens (max output: 100,000), while GLM 5.2 (Zhipu) offers 1,000,000 tokens (max output: 64,000).
At 100,000 requests per month, using o3-mini saves $204.75 every month (or $2,457.00 annually) compared to GLM 5.2 (Zhipu).
Cache the system prompt and static documentation chunks — cached input is often 4–10× cheaper. Route simple FAQ turns to a nano-tier model and escalate only complex tickets. Cap max_output per reply; support answers rarely need more than a few hundred tokens.