Simulating realistic Content generation parameters (800 in / 1,200 out with 30% cache reuse). GLM-4.5V (Z.ai) delivers a 43% cost reduction over GLM-5 (Z.ai).
| Traffic Volume Tier | GLM-5 (Z.ai) Monthly | GLM-4.5V (Z.ai) Monthly | Monthly Savings by picking GLM-4.5V (Z.ai) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $4.448 | $2.522 | Save $1.926 / mo |
| 10,000 reqs/mo (Small App) | $44.48 | $25.224 | Save $19.256 / mo |
| 100,000 reqs/mo (Growth Production) | $444.80 | $252.24 | Save $192.56 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $4,448.00 | $2,522.40 | Save $1,925.60 / mo |
GLM-4.5V (Z.ai) is 43% 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 $0.004448 on GLM-5 (Z.ai).
GLM-5 (Z.ai) offers a context window of 200,000 tokens (max output: 131,072), while GLM-4.5V (Z.ai) offers 64,000 tokens (max output: 16,384).
At 100,000 requests per month, using GLM-4.5V (Z.ai) saves $192.56 every month (or $2,310.72 annually) compared to GLM-5 (Z.ai).
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.