Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Together AI — DeepSeek V4 delivers a 58% cost reduction over Qwen 2.5 Max.
| Traffic Volume Tier | Qwen 2.5 Max Monthly | Together AI — DeepSeek V4 Monthly | Monthly Savings by picking Together AI — DeepSeek V4 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $21.632 | $9.00 | Save $12.632 / mo |
| 10,000 reqs/mo (Small App) | $216.32 | $90.00 | Save $126.32 / mo |
| 100,000 reqs/mo (Growth Production) | $2,163.20 | $900.00 | Save $1,263.20 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $21,632.00 | $9,000.00 | Save $12,632.00 / mo |
Together AI — DeepSeek V4 is 58% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Together AI — DeepSeek V4 costs $0.009 per request compared to $0.0216 on Qwen 2.5 Max.
Qwen 2.5 Max offers a context window of 32,768 tokens (max output: 8,192), while Together AI — DeepSeek V4 offers 1,000,000 tokens (max output: 64,000).
At 100,000 requests per month, using Together AI — DeepSeek V4 saves $1,263.20 every month (or $15,158.40 annually) compared to Qwen 2.5 Max.
Output is the expensive side — prefer models with cheap output for autocomplete-style calls. Cache repository context between keystrokes; diffs change far less than the full file. Measure acceptance rate: paying for output users delete is pure waste.