Simulating realistic Document summarization parameters (25,000 in / 600 out with 10% cache reuse). DeepSeek V4 Pro delivers a 39% cost reduction over GLM 4.7 (Zhipu).
| Traffic Volume Tier | DeepSeek V4 Pro Monthly | GLM 4.7 (Zhipu) Monthly | Monthly Savings by picking DeepSeek V4 Pro |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $32.186 | $52.838 | Save $20.651 / mo |
| 10,000 reqs/mo (Small App) | $321.86 | $528.375 | Save $206.515 / mo |
| 100,000 reqs/mo (Growth Production) | $3,218.60 | $5,283.75 | Save $2,065.15 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $32,186.00 | $52,837.50 | Save $20,651.50 / mo |
DeepSeek V4 Pro is 39% cheaper for Document summarization workloads. At standard Document summarization parameter ratios (25,000 input tokens, 600 output tokens, 10% cache hit), DeepSeek V4 Pro costs $0.0322 per request compared to $0.0528 on GLM 4.7 (Zhipu).
DeepSeek V4 Pro offers a context window of 1,000,000 tokens (max output: 384,000), while GLM 4.7 (Zhipu) offers 128,000 tokens (max output: 16,384).
At 100,000 requests per month, using DeepSeek V4 Pro saves $2,065.15 every month (or $24,781.80 annually) compared to GLM 4.7 (Zhipu).
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.