Simulating realistic Data extraction & tagging parameters (2,000 in / 250 out with 20% cache reuse). Databricks DBRX Instruct delivers a 19% cost reduction over Llama 3.2 90B Vision.
| Traffic Volume Tier | Llama 3.2 90B Vision Monthly | Databricks DBRX Instruct Monthly | Monthly Savings by picking Databricks DBRX Instruct |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $2.025 | $1.65 | Save $0.375 / mo |
| 10,000 reqs/mo (Small App) | $20.25 | $16.50 | Save $3.75 / mo |
| 100,000 reqs/mo (Growth Production) | $202.50 | $165.00 | Save $37.50 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $2,025.00 | $1,650.00 | Save $375.00 / mo |
Databricks DBRX Instruct is 19% cheaper for Data extraction & tagging workloads. At standard Data extraction & tagging parameter ratios (2,000 input tokens, 250 output tokens, 20% cache hit), Databricks DBRX Instruct costs $0.00165 per request compared to $0.002025 on Llama 3.2 90B Vision.
Llama 3.2 90B Vision offers a context window of 128,000 tokens (max output: 8,192), while Databricks DBRX Instruct offers 32,768 tokens (max output: 4,096).
At 100,000 requests per month, using Databricks DBRX Instruct saves $37.50 every month (or $450.00 annually) compared to Llama 3.2 90B Vision.
Volume makes nano-tier models attractive — extraction rarely needs frontier reasoning. Constrain output with JSON schema modes to avoid retry loops on malformed responses. Cache shared schema instructions and few-shot examples across calls.