Simulating realistic Customer support chatbot parameters (3,500 in / 350 out with 70% cache reuse). Databricks DBRX Instruct delivers a 62% cost reduction over GPT-5.3 Codex.
| Traffic Volume Tier | GPT-5.3 Codex Monthly | Databricks DBRX Instruct Monthly | Monthly Savings by picking Databricks DBRX Instruct |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $7.166 | $2.73 | Save $4.436 / mo |
| 10,000 reqs/mo (Small App) | $71.663 | $27.30 | Save $44.363 / mo |
| 100,000 reqs/mo (Growth Production) | $716.625 | $273.00 | Save $443.625 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $7,166.25 | $2,730.00 | Save $4,436.25 / mo |
Databricks DBRX Instruct is 62% cheaper for Customer support chatbot workloads. At standard Customer support chatbot parameter ratios (3,500 input tokens, 350 output tokens, 70% cache hit), Databricks DBRX Instruct costs $0.00273 per request compared to $0.007166 on GPT-5.3 Codex.
GPT-5.3 Codex offers a context window of 256,000 tokens (max output: 64,000), while Databricks DBRX Instruct offers 32,768 tokens (max output: 4,096).
At 100,000 requests per month, using Databricks DBRX Instruct saves $443.625 every month (or $5,323.50 annually) compared to GPT-5.3 Codex.
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.