Using USD display for price cards and history values.

Latest snapshot Apr 13, 22:05 Most recent stored public pricing point for this model.
Source PricePerToken OpenAI Source page Keep the source link visible so the latest stored number stays manually verifiable.
Source mode Fallback source Verified fallback is in use because the preferred official page is not consistently crawlable right now.
History signal Warming up Tracking is still warming up. 2 stored points across 14 days. 30d and 90d windows are still awaiting depth.
Cached pricing $0.0050 Cached input pricing only appears when the source exposes it clearly.
Batch discount Not listed Shown only when a provider-listed batch price is normalized. Do not mix it with realtime pricing assumptions.
Latest move No recent delta No recent delta has been detected between the latest two stored snapshots.
Stored history 2 points · 14 days First comparison. You can compare the latest move, but longer windows are still thin and may overstate short-term noise.
Strongest window 7d change looks flat This window looks stable. Use the current price card and broader history depth to decide.
Recommended next step Open compare There is enough recent context to compare this model against alternatives rather than looking at a single price card.
Input price
$0.050 per 1M tokens
Output price
$0.400 per 1M tokens
Cached input
$0.0050 per 1M tokens
Blended price
$0.138 75 / 25 input-output mix
Single request estimate $0.0005
Monthly estimate $144.60
Batch discount Not listed
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.

You can compare the latest move, but longer windows are still thin and may overstate short-term noise.

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.

You can compare the latest move, but longer windows are still thin and may overstate short-term noise.

7d change Apr 6, 22:05 -> Apr 13, 22:05
Input 0% Output 0% Cached 0%
5 stored points across 7 days This window looks stable. Use the current price card and broader history depth to decide.
30d change Awaiting depth Awaiting depth Needs 30+ days of stored snapshots.
90d change Awaiting depth Awaiting depth Needs 90+ days of stored snapshots.
Tracking span Mar 30, 12:00 -> Apr 13, 22:05 14 stored days covered by the visible history.
Latest detected change No change yet Driven only by stored deltas, not guessed from one point.
History status First comparison You can compare the latest move, but longer windows are still thin and may overstate short-term noise.
Input Output Cached

Shared scale across visible pricing lines. Use the table below for exact values.

Captured at Input / 1M Output / 1M Cached / 1M Source
Mar 30, 12:00 $0.050 $0.400 $0.0050 OpenAI
Apr 13, 22:05 $0.050 $0.400 $0.0050 PricePerToken OpenAI
No event log yet Waiting for a detected change A change log entry appears only when a newer snapshot differs from the previous stored point.

Source and limits

Source PricePerToken OpenAI PricePerToken OpenAI
Recorded check Checked Apr 13, 22:05
Parser version pricepertoken-payload-v1
Context window 400000
Output limit 128000
Trust policy This page stays official-first whenever the provider page is crawlable. If not, verified fallback or baseline states stay explicit so the source trace never over-claims a live official crawl.
Source note Fallback snapshot from PricePerToken because OpenAI official pricing pages currently return an anti-bot challenge to server-side crawlers. Source updated at 2026-04-12T09:23:55.468156Z.

When this model detail is enough

Use this page when you need a single-model read: current price, source traceability, recent change strength, and enough stored history to judge whether the latest move is actionable.

When to escalate to compare

If a recent price cut or a stable multi-point window makes this model newly competitive, move to compare so every candidate runs against the same workload assumptions.

When to escalate to calculator

If a recent price increase changes spend assumptions or history is still thin, use calculator next so you can replace the reference workload with your own traffic, cache ratio, and budget ceiling.