Simulating realistic Content generation parameters (800 in / 1,200 out with 30% cache reuse). DeepSeek Coder V2.5 delivers a 91% cost reduction over GLM 4.7 (Zhipu).
| Traffic Volume Tier | DeepSeek Coder V2.5 Monthly | GLM 4.7 (Zhipu) Monthly | Monthly Savings by picking DeepSeek Coder V2.5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $0.4178 | $4.614 | Save $4.196 / mo |
| 10,000 reqs/mo (Small App) | $4.178 | $46.14 | Save $41.962 / mo |
| 100,000 reqs/mo (Growth Production) | $41.776 | $461.40 | Save $419.624 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $417.76 | $4,614.00 | Save $4,196.24 / mo |
DeepSeek Coder V2.5 is 91% cheaper for Content generation workloads. At standard Content generation parameter ratios (800 input tokens, 1,200 output tokens, 30% cache hit), DeepSeek Coder V2.5 costs $0.000418 per request compared to $0.004614 on GLM 4.7 (Zhipu).
DeepSeek Coder V2.5 offers a context window of 128,000 tokens (max output: 8,192), while GLM 4.7 (Zhipu) offers 128,000 tokens (max output: 16,384).
At 100,000 requests per month, using DeepSeek Coder V2.5 saves $419.624 every month (or $5,035.488 annually) compared to GLM 4.7 (Zhipu).
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.