Simulating realistic Content generation parameters (800 in / 1,200 out with 30% cache reuse). Codestral 2508 (OpenRouter) delivers a 58% cost reduction over GLM-4.5 (Z.ai).
| Traffic Volume Tier | GLM-4.5 (Z.ai) Monthly | Codestral 2508 (OpenRouter) Monthly | Monthly Savings by picking Codestral 2508 (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $3.002 | $1.255 | Save $1.747 / mo |
| 10,000 reqs/mo (Small App) | $30.024 | $12.552 | Save $17.472 / mo |
| 100,000 reqs/mo (Growth Production) | $300.24 | $125.52 | Save $174.72 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $3,002.40 | $1,255.20 | Save $1,747.20 / mo |
Codestral 2508 (OpenRouter) is 58% cheaper for Content generation workloads. At standard Content generation parameter ratios (800 input tokens, 1,200 output tokens, 30% cache hit), Codestral 2508 (OpenRouter) costs $0.001255 per request compared to $0.003002 on GLM-4.5 (Z.ai).
GLM-4.5 (Z.ai) offers a context window of 128,000 tokens (max output: 98,304), while Codestral 2508 (OpenRouter) offers 256,000 tokens (max output: 204,800).
At 100,000 requests per month, using Codestral 2508 (OpenRouter) saves $174.72 every month (or $2,096.64 annually) compared to GLM-4.5 (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.