Simulating realistic Document summarization parameters (25,000 in / 600 out with 10% cache reuse). Codestral 2501 delivers a 79% cost reduction over GLM-5.1 (Z.ai).
| Traffic Volume Tier | Codestral 2501 Monthly | GLM-5.1 (Z.ai) Monthly | Monthly Savings by picking Codestral 2501 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $7.365 | $34.79 | Save $27.425 / mo |
| 10,000 reqs/mo (Small App) | $73.65 | $347.90 | Save $274.25 / mo |
| 100,000 reqs/mo (Growth Production) | $736.50 | $3,479.00 | Save $2,742.50 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $7,365.00 | $34,790.00 | Save $27,425.00 / mo |
Codestral 2501 is 79% cheaper for Document summarization workloads. At standard Document summarization parameter ratios (25,000 input tokens, 600 output tokens, 10% cache hit), Codestral 2501 costs $0.007365 per request compared to $0.0348 on GLM-5.1 (Z.ai).
Codestral 2501 offers a context window of 256,000 tokens (max output: 8,192), while GLM-5.1 (Z.ai) offers 200,000 tokens (max output: 131,072).
At 100,000 requests per month, using Codestral 2501 saves $2,742.50 every month (or $32,910.00 annually) compared to GLM-5.1 (Z.ai).
Long-context models pay off here — compare price per 1M tokens at your true document size. Summarize once, store the result; don't re-summarize unchanged documents. For batch backfills, nightly jobs can use cache-friendly request ordering.