Simulating realistic Data extraction & tagging parameters (2,000 in / 250 out with 20% cache reuse). GPT-5.3 Codex delivers a 93% cost reduction over GPT-5.5 Pro.
| Traffic Volume Tier | GPT-5.5 Pro Monthly | GPT-5.3 Codex Monthly | Monthly Savings by picking GPT-5.3 Codex |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $94.20 | $6.37 | Save $87.83 / mo |
| 10,000 reqs/mo (Small App) | $942.00 | $63.70 | Save $878.30 / mo |
| 100,000 reqs/mo (Growth Production) | $9,420.00 | $637.00 | Save $8,783.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $94,200.00 | $6,370.00 | Save $87,830.00 / mo |
GPT-5.3 Codex is 93% cheaper for Data extraction & tagging workloads. At standard Data extraction & tagging parameter ratios (2,000 input tokens, 250 output tokens, 20% cache hit), GPT-5.3 Codex costs $0.00637 per request compared to $0.0942 on GPT-5.5 Pro.
GPT-5.5 Pro offers a context window of 512,000 tokens (max output: 64,000), while GPT-5.3 Codex offers 256,000 tokens (max output: 64,000).
At 100,000 requests per month, using GPT-5.3 Codex saves $8,783.00 every month (or $105,396.00 annually) compared to GPT-5.5 Pro.
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.