Simulating realistic Translation parameters (5,000 in / 5,500 out with 15% cache reuse). DeepSeek Coder V2.5 delivers a 90% cost reduction over GLM-5 (Z.ai).
| Traffic Volume Tier | DeepSeek Coder V2.5 Monthly | GLM-5 (Z.ai) Monthly | Monthly Savings by picking DeepSeek Coder V2.5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $2.146 | $22.00 | Save $19.855 / mo |
| 10,000 reqs/mo (Small App) | $21.455 | $220.00 | Save $198.545 / mo |
| 100,000 reqs/mo (Growth Production) | $214.55 | $2,200.00 | Save $1,985.45 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $2,145.50 | $22,000.00 | Save $19,854.50 / mo |
DeepSeek Coder V2.5 is 90% cheaper for Translation workloads. At standard Translation parameter ratios (5,000 input tokens, 5,500 output tokens, 15% cache hit), DeepSeek Coder V2.5 costs $0.002146 per request compared to $0.022 on GLM-5 (Z.ai).
DeepSeek Coder V2.5 offers a context window of 128,000 tokens (max output: 8,192), while GLM-5 (Z.ai) offers 200,000 tokens (max output: 131,072).
At 100,000 requests per month, using DeepSeek Coder V2.5 saves $1,985.45 every month (or $23,825.40 annually) compared to GLM-5 (Z.ai).
Output length ≈ input length; budget both sides of the request. Japanese and Chinese text typically costs more per word than English due to tokenization. Cache translation memories and glossaries embedded in the prompt.