Simulating realistic Translation parameters (5,000 in / 5,500 out with 15% cache reuse). DeepSeek V3 (Chat) delivers a 46% cost reduction over GPT-4o mini.
Quick answer
For Translation, DeepSeek V3 (Chat) is the lower-cost option at $0.002146 per request versus $0.003994 for GPT-4o mini, a modeled saving of 46%.
Method & trust
The comparison uses 5,000 input tokens, 5,500 output tokens, and 15% cache reuse for the selected workload. Pricing is applied per model, then scaled to monthly request volumes.
| Traffic Volume Tier | DeepSeek V3 (Chat) Monthly | GPT-4o mini Monthly | Monthly Savings by picking DeepSeek V3 (Chat) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $2.146 | $3.994 | Save $1.848 / mo |
| 10,000 reqs/mo (Small App) | $21.455 | $39.938 | Save $18.482 / mo |
| 100,000 reqs/mo (Growth Production) | $214.55 | $399.375 | Save $184.825 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $2,145.50 | $3,993.75 | Save $1,848.25 / mo |
DeepSeek V3 (Chat) is 46% cheaper for Translation workloads. At standard Translation parameter ratios (5,000 input tokens, 5,500 output tokens, 15% cache hit), DeepSeek V3 (Chat) costs $0.002146 per request compared to $0.003994 on GPT-4o mini.
DeepSeek V3 (Chat) offers a context window of 64,000 tokens (max output: 8,000), while GPT-4o mini offers 128,000 tokens (max output: 16,384).
At 100,000 requests per month, using DeepSeek V3 (Chat) saves $184.825 every month (or $2,217.90 annually) compared to GPT-4o mini.
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.