Simulating realistic Data extraction & tagging parameters (2,000 in / 250 out with 20% cache reuse). o4-mini delivers a 30% cost reduction over Qwen 2.5 Max.
| Traffic Volume Tier | o4-mini Monthly | Qwen 2.5 Max Monthly | Monthly Savings by picking o4-mini |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $2.97 | $4.224 | Save $1.254 / mo |
| 10,000 reqs/mo (Small App) | $29.70 | $42.24 | Save $12.54 / mo |
| 100,000 reqs/mo (Growth Production) | $297.00 | $422.40 | Save $125.40 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $2,970.00 | $4,224.00 | Save $1,254.00 / mo |
o4-mini is 30% cheaper for Data extraction & tagging workloads. At standard Data extraction & tagging parameter ratios (2,000 input tokens, 250 output tokens, 20% cache hit), o4-mini costs $0.00297 per request compared to $0.004224 on Qwen 2.5 Max.
o4-mini offers a context window of 256,000 tokens (max output: 100,000), while Qwen 2.5 Max offers 32,768 tokens (max output: 8,192).
At 100,000 requests per month, using o4-mini saves $125.40 every month (or $1,504.80 annually) compared to Qwen 2.5 Max.
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.