Simulating realistic Translation parameters (5,000 in / 5,500 out with 15% cache reuse). DeepSeek Coder V2.5 delivers a 96% cost reduction over Gemini 3.5 Flash (OpenRouter).
| Traffic Volume Tier | DeepSeek Coder V2.5 Monthly | Gemini 3.5 Flash (OpenRouter) Monthly | Monthly Savings by picking DeepSeek Coder V2.5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $2.146 | $55.988 | Save $53.842 / mo |
| 10,000 reqs/mo (Small App) | $21.455 | $559.875 | Save $538.42 / mo |
| 100,000 reqs/mo (Growth Production) | $214.55 | $5,598.75 | Save $5,384.20 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $2,145.50 | $55,987.50 | Save $53,842.00 / mo |
DeepSeek Coder V2.5 is 96% 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 $0.056 on Gemini 3.5 Flash (OpenRouter).
DeepSeek Coder V2.5 offers a context window of 128,000 tokens (max output: 8,192), while Gemini 3.5 Flash (OpenRouter) offers 1,048,576 tokens (max output: 65,536).
At 100,000 requests per month, using DeepSeek Coder V2.5 saves $5,384.20 every month (or $64,610.40 annually) compared to Gemini 3.5 Flash (OpenRouter).
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.