Simulating realistic Customer support chatbot parameters (3,500 in / 350 out with 70% cache reuse). Devstral 2 (2512) (OpenRouter) delivers a 21% cost reduction over DeepSeek R1 (Reasoner).
| Traffic Volume Tier | DeepSeek R1 (Reasoner) Monthly | Devstral 2 (2512) (OpenRouter) Monthly | Monthly Savings by picking Devstral 2 (2512) (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $1.687 | $1.34 | Save $0.3472 / mo |
| 10,000 reqs/mo (Small App) | $16.87 | $13.398 | Save $3.472 / mo |
| 100,000 reqs/mo (Growth Production) | $168.70 | $133.98 | Save $34.72 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $1,687.00 | $1,339.80 | Save $347.20 / mo |
Devstral 2 (2512) (OpenRouter) is 21% cheaper for Customer support chatbot workloads. At standard Customer support chatbot parameter ratios (3,500 input tokens, 350 output tokens, 70% cache hit), Devstral 2 (2512) (OpenRouter) costs $0.00134 per request compared to $0.001687 on DeepSeek R1 (Reasoner).
DeepSeek R1 (Reasoner) offers a context window of 64,000 tokens (max output: 8,000), while Devstral 2 (2512) (OpenRouter) offers 262,144 tokens (max output: 209,715).
At 100,000 requests per month, using Devstral 2 (2512) (OpenRouter) saves $34.72 every month (or $416.64 annually) compared to DeepSeek R1 (Reasoner).
Cache the system prompt and static documentation chunks — cached input is often 4–10× cheaper. Route simple FAQ turns to a nano-tier model and escalate only complex tickets. Cap max_output per reply; support answers rarely need more than a few hundred tokens.