Simulating realistic Customer support chatbot parameters (3,500 in / 350 out with 70% cache reuse). Codestral 2508 (OpenRouter) delivers a 58% cost reduction over DeepSeek R1 (Reasoner).
| Traffic Volume Tier | DeepSeek R1 (Reasoner) Monthly | Codestral 2508 (OpenRouter) Monthly | Monthly Savings by picking Codestral 2508 (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $1.687 | $0.7035 | Save $0.9835 / mo |
| 10,000 reqs/mo (Small App) | $16.87 | $7.035 | Save $9.835 / mo |
| 100,000 reqs/mo (Growth Production) | $168.70 | $70.35 | Save $98.35 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $1,687.00 | $703.50 | Save $983.50 / mo |
Codestral 2508 (OpenRouter) is 58% cheaper for Customer support chatbot workloads. At standard Customer support chatbot parameter ratios (3,500 input tokens, 350 output tokens, 70% cache hit), Codestral 2508 (OpenRouter) costs $0.000703 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 Codestral 2508 (OpenRouter) offers 256,000 tokens (max output: 204,800).
At 100,000 requests per month, using Codestral 2508 (OpenRouter) saves $98.35 every month (or $1,180.20 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.