Simulating realistic Document summarization parameters (25,000 in / 600 out with 10% cache reuse). Mistral Medium 3.5 delivers a 31% cost reduction over GLM-4.5-X (Z.ai).
| Traffic Volume Tier | Mistral Medium 3.5 Monthly | GLM-4.5-X (Z.ai) Monthly | Monthly Savings by picking Mistral Medium 3.5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $38.625 | $55.965 | Save $17.34 / mo |
| 10,000 reqs/mo (Small App) | $386.25 | $559.65 | Save $173.40 / mo |
| 100,000 reqs/mo (Growth Production) | $3,862.50 | $5,596.50 | Save $1,734.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $38,625.00 | $55,965.00 | Save $17,340.00 / mo |
Mistral Medium 3.5 is 31% cheaper for Document summarization workloads. At standard Document summarization parameter ratios (25,000 input tokens, 600 output tokens, 10% cache hit), Mistral Medium 3.5 costs $0.0386 per request compared to $0.056 on GLM-4.5-X (Z.ai).
Mistral Medium 3.5 offers a context window of 256,000 tokens (max output: 32,768), while GLM-4.5-X (Z.ai) offers 128,000 tokens (max output: 98,304).
At 100,000 requests per month, using Mistral Medium 3.5 saves $1,734.00 every month (or $20,808.00 annually) compared to GLM-4.5-X (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.