Simulating realistic Content generation parameters (800 in / 1,200 out with 30% cache reuse). GLM-4.5V (Z.ai) delivers a 13% cost reduction over Devstral 2 (2512) (OpenRouter).
| Traffic Volume Tier | GLM-4.5V (Z.ai) Monthly | Devstral 2 (2512) (OpenRouter) Monthly | Monthly Savings by picking GLM-4.5V (Z.ai) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $2.522 | $2.897 | Save $0.3746 / mo |
| 10,000 reqs/mo (Small App) | $25.224 | $28.97 | Save $3.746 / mo |
| 100,000 reqs/mo (Growth Production) | $252.24 | $289.696 | Save $37.456 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $2,522.40 | $2,896.96 | Save $374.56 / mo |
GLM-4.5V (Z.ai) is 13% cheaper for Content generation workloads. At standard Content generation parameter ratios (800 input tokens, 1,200 output tokens, 30% cache hit), GLM-4.5V (Z.ai) costs $0.002522 per request compared to $0.002897 on Devstral 2 (2512) (OpenRouter).
GLM-4.5V (Z.ai) offers a context window of 64,000 tokens (max output: 16,384), while Devstral 2 (2512) (OpenRouter) offers 262,144 tokens (max output: 209,715).
At 100,000 requests per month, using GLM-4.5V (Z.ai) saves $37.456 every month (or $449.472 annually) compared to Devstral 2 (2512) (OpenRouter).
Output-heavy workloads favor models with a low output price, not a low input price. Batch similar generation tasks with shared style prompts to exploit caching. Draft with a cheap tier, refine the winners with a premium model.