OpenAI API Pricing: GPT-5.4, GPT-5.2, and GPT-5.1 (April 2026)

OpenAI's public pricing changed enough in 2026 that broad comparison tables age badly. This guide sticks to what OpenAI currently publishes in official docs: the live API pricing page for the GPT-5.4 family, and the GPT-5.2 launch page for GPT-5.2, GPT-5.1, and GPT-5 Pro pricing.

Use our cost calculator for quick estimates and our token counter to sanity-check prompt size before you ship.

Current OpenAI pricing at a glance

GPT-5.4 family on the live pricing page

Model	Input $/M	Cached Input $/M	Output $/M
GPT-5.4	$2.50	$0.25	$15.00
GPT-5.4 mini	$0.75	$0.075	$4.50
GPT-5.4 nano	$0.20	$0.02	$1.25

OpenAI notes that those rates are the standard processing rates for context lengths under 270K.

GPT-5.2 and earlier GPT-5 pricing still published by OpenAI

Model	Input $/M	Cached Input $/M	Output $/M
GPT-5.2	$1.75	$0.175	$14.00
GPT-5.2 Pro	$21.00	-	$168.00
GPT-5.1	$1.25	$0.125	$10.00
GPT-5 Pro	$15.00	-	$120.00

OpenAI also says it has no current plans to deprecate GPT-5.1, GPT-5, or GPT-4.1 in the API, which is why those older rows still matter for real production systems.

What to start with

For most teams, the order is straightforward:

1. Start with GPT-5.4 nano if your workload is high-volume and easy to review.
2. Move to GPT-5.4 mini if nano misses too often or your task needs stronger coding and reasoning.
3. Use GPT-5.4 when quality matters enough to justify the step up.
4. Reserve GPT-5.2 Pro or GPT-5 Pro for workloads where you have measured a clear win that pays for the premium.

That is the practical answer. Most teams overspend by defaulting to the flagship tier before they have an eval set.

Real cost example: the same workload on GPT-5.4, mini, and nano

Assume a coding assistant handling 1,000 requests per day, with 2,000 input tokens and 500 output tokens per request.

GPT-5.4

• Daily input: 1,000 x 2,000 x $2.50 / 1M = $5.00
• Daily output: 1,000 x 500 x $15.00 / 1M = $7.50
• Monthly total: about $375

GPT-5.4 mini

• Daily input: 1,000 x 2,000 x $0.75 / 1M = $1.50
• Daily output: 1,000 x 500 x $4.50 / 1M = $2.25
• Monthly total: about $112.50

GPT-5.4 nano

• Daily input: 1,000 x 2,000 x $0.20 / 1M = $0.40
• Daily output: 1,000 x 500 x $1.25 / 1M = $0.625
• Monthly total: about $30.75

That is why OpenAI's cheapest tier is worth testing first. The gap from GPT-5.4 to GPT-5.4 nano on this workload is more than 12x.

Cached input and Batch API are the two easiest savings

Cached input

For the GPT-5.4 family, cached input is priced at exactly 10% of normal input cost:

• GPT-5.4: $0.25 instead of $2.50
• GPT-5.4 mini: $0.075 instead of $0.75
• GPT-5.4 nano: $0.02 instead of $0.20

If your app reuses the same system prompt, policy block, or large shared prefix, that discount matters immediately.

Batch API

OpenAI's live pricing page says the Batch API cuts both input and output prices by 50%. That means the $375/month GPT-5.4 example above drops to roughly $187.50/month if the workload can tolerate asynchronous processing.

If you are generating large volumes of SEO pages, support summaries, or offline enrichment jobs, Batch is usually the first optimization to enable.

One pricing caveat to keep in mind

OpenAI's pricing page also says data residency and Regional Processing endpoints add 10% for all models released after March 5, 2026. If you have compliance-driven routing, do not ignore that surcharge when you model spend.

The practical takeaway

If you just want the shortest path to a sane OpenAI bill:

• Test GPT-5.4 nano first.
• Step up to GPT-5.4 mini before you jump to the flagship model.
• Use GPT-5.4 when the eval set proves the upgrade is worth it.
• Turn on cached inputs and Batch API before you start hunting for smaller prompt wins.

For a provider-level comparison across multiple vendors, see our LLM pricing overview.