How much does a ChatGPT subscription cost?

As of August 2026: Free at $0, Go at $8/month (ad-supported, limited features), Plus at $20/month, Pro at $100/month (5x Plus usage) or $200/month (20x Plus usage), Business at $20/user/month billed annually and Enterprise at custom pricing.

How much does the OpenAI API cost per million tokens?

As of August 2026, within the GPT-5.6 family: gpt-5.6-luna costs $0.10 input / $0.60 output per million tokens, gpt-5.6-terra $1/$6 and gpt-5.6-sol $2.50/$15. The coding model gpt-5.3-codex costs $1.75/$14. The Batch API halves these rates and cached input is billed at 10% of the input price.

Should I use a ChatGPT subscription or the OpenAI API?

A subscription fits humans working interactively in ChatGPT or Codex, at a predictable per-seat price. The API fits software calling models without a person watching: chatbots, document pipelines, agents and CI jobs. API costs scale with usage rather than headcount.

How can I reduce OpenAI API costs?

Match the model to the task (the spread inside the GPT-5.6 family is 25x), use the Batch API for asynchronous jobs (50% discount), cache repeated context (10% of the input price), govern the multipliers (Fast mode 4x, long context 2x, data residency 1.1x) and, on Azure OpenAI, compare PAYG against reservation-discounted PTUs at your real utilization.

OpenAI Pricing Explained: ChatGPT Subscription or API, and When Each Makes Sense

il y a 21 heures
4 min de lecture

OpenAI sells its models 2 ways, under 2 different names. ChatGPT is the subscription product, billed per person per month. The OpenAI API is the developer platform, billed per token consumed. The distinction matters because the same question, “what does GPT cost?”, has 2 unrelated answers depending on which one you mean. This post covers both, plus the third channel most enterprises meet: the same models resold through Microsoft Azure.

All prices are as of August 2026.

Subscription pricing: a flat fee per person

A subscription gives a named person access through the ChatGPT apps, including agents, Deep Research and the Codex coding environment.

Plan	Price	What it adds
Free	$0	Limited messages on the standard model
Go	$8/month	Unlimited standard model, ad-supported, no advanced features
Plus	$20/month	Extended GPT-5.x access, agents, Deep Research quota
Pro	$100/month	5x Plus usage, elevated Codex limits
Pro	$200/month	20x Plus usage, the highest individual tier
Business	$20/user/month billed annually ($25 monthly, 2-user minimum)	Admin console, SAML SSO, no training on your data
Enterprise	Custom, via sales	Compliance features, custom retention, negotiated usage

A calibration note on this table:

OpenAI does not publish one consolidated price page for all plans, so these figures are cross-checked across 2 independent pricing trackers dated July and August 2026.

The structure moved twice this year: the Pro tier split into $100 and $200 versions on April 9, 2026, and the $8 ad-supported Go plan is rolling out by region.

The pattern to retain is the same as at Anthropic: a flat fee with a usage ceiling, and heavy users pay for a higher ceiling rather than per token. The ceiling is not a monthly quota, and it is not contractual on individual plans: limits reset on rolling windows of 3 to 5 hours depending on plan and model, some features carry weekly or monthly quotas on top, and OpenAI states that the values themselves may vary with demand, system conditions and individual usage.

API pricing: pay per token

The API is how software calls OpenAI models. Billing is per token, a fragment of text of roughly 3/4 of an English word, counted separately for input and output. Prices are per million tokens (MTok).

Model	Input ($/MTok)	Output ($/MTok)	Role
gpt-5.6-luna	$0.10	$0.60	Small, high-volume tasks
gpt-5.6-terra	$1.00	$6.00	Balanced default
gpt-5.3-codex	$1.75	$14.00	Coding
gpt-5.6-sol	$2.50	$15.00	Flagship reasoning

Bar chart of OpenAI API prices per million tokens in August 2026: gpt-5.6-luna at $0.10 input and $0.60 output, gpt-5.6-terra at $1 and $6, gpt-5.3-codex at $1.75 and $14, gpt-5.6-sol at $2.50 and $15, a 25x spread across the GPT-5.6 family.

The base rate is only the anchor. The Batch API, for jobs that can wait, cuts both prices by 50%. Cached input is billed at 10% of the input price, and cache writes cost 25% above it. Then come the multipliers: Fast mode (formerly priority processing) at 4x the standard rate, long-context variants at 2x and regional data residency at 1.1x. Web search costs $10 per 1,000 calls, file search $2.50 per 1,000 calls plus $0.10 per GB-day of storage.

Enterprises often meet these models through a third door: Azure OpenAI Service. Microsoft resells the same model families with its own price sheet, its own data-residency options and a capacity model of its own, Provisioned Throughput Units, which can be reserved for 1 month to 3 years at a discount. Billing lands on the Azure invoice, not an OpenAI one. The models match, the FinOps mechanics do not.

When a subscription is the right choice

A subscription fits when a human is in the loop: chat, analysis, documents and coding sessions in Codex. A developer working in Codex all day is the clearest case, and it is why the $100 Pro tier is built around elevated Codex limits. The seat price caps a consumption that would be open-ended through the API.

Predictability carries the same weight as at any AI vendor. Finance can budget seats. Budgeting tokens for 40 people requires a forecast, and forecasts of individual usage carry wide error bars.

When the API is the right choice

The API fits when software calls the model without a person watching: a support chatbot, a document pipeline, an agent, a CI job. A subscription authenticates a person, not an application, so these workloads have no subscription path.

API spend scales with traffic and agent activity instead of headcount. A pipeline that doubles its volume doubles its bill, and nobody approves the increase.

5 ways to keep OpenAI costs under control

Match the model to the task. The spread inside the GPT-5.6 family is 25x: $0.10 against $2.50 on input, $0.60 against $15 on output. Classification, extraction and routing belong on luna, not sol.
Batch what can wait. Nightly document processing and evaluation runs qualify for the Batch API and its 50% discount.
Cache repeated context. System prompts and shared reference documents reread at 10% of the input price.
Govern the multipliers. Fast mode at 4x, long context at 2x and residency at 1.1x stack on top of each other and on top of model choice. Decide who may enable Fast mode, and keep it out of batch jobs and CI. We wrote the same warning about Anthropic's Fast mode; the pattern is now industry-wide.
On Azure, compare the right numbers. Hourly PTUs at full utilization can cost more than pay-as-you-go tokens; the comparison that matters is reservation-discounted PTUs against your actual utilization curve. Run it before concluding provisioned capacity is uneconomic, and before buying a reservation locked to the wrong locality.

Where to start

The inventory is the same exercise as for any AI vendor: who holds a paid seat, which workloads hold an API key, which model each one calls, and, if Azure is involved, which subscription the tokens land on. One addition specific to OpenAI: note who sits on the $200 Pro tier and whether their usage justifies 20x Plus. A seat downgraded from $200 to $20 pays for itself in the first month, and the invoice will confirm it.

The FinOps skill OptimNow uses to track AI vendor billing is open source under CC BY-SA: github.com/OptimNow/cloud-finops-skills. Download it, load it into your own Claude and run the same analysis on your invoice.

Sources

OpenAI API pricing documentation, OpenAI

ChatGPT pricing tracker, Gradually, July 2026

ChatGPT pricing comparison, CometAPI