Simulating realistic Content generation parameters (800 in / 1,200 out with 30% cache reuse). DeepInfra — Qwen 2.5 Coder 32B delivers a 92% cost reduction over Kimi K2.7 Code (OpenRouter).
| Traffic Volume Tier | Kimi K2.7 Code (OpenRouter) Monthly | DeepInfra — Qwen 2.5 Coder 32B Monthly | Monthly Savings by picking DeepInfra — Qwen 2.5 Coder 32B |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $4.501 | $0.352 | Save $4.149 / mo |
| 10,000 reqs/mo (Small App) | $45.008 | $3.52 | Save $41.488 / mo |
| 100,000 reqs/mo (Growth Production) | $450.08 | $35.20 | Save $414.88 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $4,500.80 | $352.00 | Save $4,148.80 / mo |
DeepInfra — Qwen 2.5 Coder 32B is 92% cheaper for Content generation workloads. At standard Content generation parameter ratios (800 input tokens, 1,200 output tokens, 30% cache hit), DeepInfra — Qwen 2.5 Coder 32B costs $0.000352 per request compared to $0.004501 on Kimi K2.7 Code (OpenRouter).
Kimi K2.7 Code (OpenRouter) offers a context window of 262,144 tokens (max output: 235,929), while DeepInfra — Qwen 2.5 Coder 32B offers 128,000 tokens (max output: 8,192).
At 100,000 requests per month, using DeepInfra — Qwen 2.5 Coder 32B saves $414.88 every month (or $4,978.56 annually) compared to Kimi K2.7 Code (OpenRouter).
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.