Latest snapshot Mar 30, 12:00 Most recent stored public pricing point for this model.
Source OpenAI Official source Keep the source link visible so the latest stored number stays manually verifiable.
Last verified Verified Mar 30, 12:00 Verification time may match the snapshot time or an earlier manual baseline date.
Cached pricing $0.25 Cached input pricing only appears when the source exposes it clearly.
Batch discount -50% Batch mode should not be mixed with realtime pricing assumptions.
Input price
$2.50 per 1M tokens
Output price
$15.00 per 1M tokens
Cached input
$0.25 per 1M tokens
Blended price
$5.625 75 / 25 input-output mix
Single request estimate $0.0191
Monthly estimate $5730.00
Batch discount -50%
How to read this estimate The reference workload is a fast sanity check, not a forecast. If your prompt shape, cache ratio, or monthly traffic differs, jump to the calculator with this model preselected and adjust the assumptions there.
No delta yet Waiting for another snapshot A price change needs at least two recorded points. This model currently has too little history to show a delta or nothing has changed yet.

Only one stored point exists so far. Trend and change detection will become useful after later crawls add more history.

Captured at Input / 1M Output / 1M Cached / 1M Source
Mar 30, 12:00 $2.50 $15.00 $0.25 OpenAI

Source and limits

Source OpenAI OpenAI
Last verified Verified Mar 30, 12:00
Context window 400000
Output limit 128000
Source note Official OpenAI pricing baseline manually verified against https://openai.com/api/pricing/ and https://developers.openai.com/api/docs/models/all on 2026-03-30. Stored as a bootstrap snapshot because the official pricing page may return an anti-bot challenge to server-side crawlers. Batch pricing is modeled as 50% of normal input/output pricing where OpenAI lists Batch API support.

When this model detail is enough

Use this page when you need a single-model read: current price, context limits, source traceability, and a lightweight history view without opening the full comparison workflow.

When to escalate to compare

If you are choosing between several plausible models, one detail page is not enough. Move to compare so every candidate runs against the same workload assumptions.

When to escalate to calculator

If finance or usage planning matters, use calculator next. That lets you replace the reference workload with your own request volume, cache ratio, and budget ceiling.