GPT-5.5 pricing is double GPT-5.4 per token, and we think the claim that it makes up for that with fewer tokens is the one to test, not the one to trust. Run 20 of your own tasks on both models and judge by cost per finished job.
The short version
Our verdict is that the doubled rate is real and the offsetting saving is unproven for you. According to OpenAI’s launch page, GPT-5.5 lists at $5 per million input tokens and $30 per million output tokens. GPT-5.4, launched in March, was $2.50 and $15, and Claude Opus 4.7 lists at $5 and $25.
OpenAI says GPT-5.5 is more token efficient and delivers frontier coding intelligence at half the cost of competitors, citing Artificial Analysis. A doubled rate needs a very large token reduction to break even, and the reduction varies by task.
Divide total spend by tasks completed correctly, on both models, before you switch anything.
GPT-5.5 pricing may not double your bill, because OpenAI argues the model finishes tasks with fewer tokens. Whether it does depends on your prompts, and an afternoon of testing will tell you.
What does GPT-5.5 pricing look like?
The standard API rate is $5 per million input tokens and $30 per million output tokens. GPT-5.5 Pro costs $30 and $180. Batch and Flex processing cost half the standard rate, and Priority processing costs 2.5 times it. The API context window is 1 million tokens, according to OpenAI, which added the API availability in an update dated 24 April after the main announcement said it was coming soon.
Anthropic’s Claude Opus 4.7, released about a week earlier, lists at $5 input and $25 output. On sticker price alone, GPT-5.5 costs the same on input and 20% more on output. Anthropic also warns that Opus 4.7’s new tokenizer can map the same text to between 1.0 and 1.35 times as many tokens, so list prices alone don’t settle that comparison either.
Do fewer tokens make up for a doubled rate?
Only if the drop is very big, and bigger than most people expect. Here is a worked example, with the arithmetic shown so you can swap in your own numbers. It’s our illustration, not a measurement. Say a task sends 3,000 tokens in and gets 1,000 back, and you run 1,000 of them.
- GPT-5.4: 3 million input tokens at $2.50 is $7.50, and 1 million output tokens at $15 is $15. Total $22.50.
- GPT-5.5 with identical token counts: $15 plus $30. Total $45.
- GPT-5.5 if output falls 40%: $15 plus $18. Total $33.
- GPT-5.5 if output falls 50%: $15 plus $15. Total $30.
Even a halved output leaves the bill 33% above GPT-5.4’s. To land at $22.50 on this mix, output would have to fall by 75%, because the 3,000 input tokens don’t shrink when the model gets more efficient. It’s like a car that gets better mileage but needs a more expensive tank of fuel. The mileage has to improve a lot before you save anything.
That doesn’t make OpenAI’s claim false. Reasoning models spend a lot of tokens thinking, and on long, hard jobs the saving can be large. It does mean the claim shouldn’t be accepted as a general rule.
What do the benchmarks say, and who ran them?
OpenAI’s own table has GPT-5.5 at 82.7% on Terminal-Bench 2.0 against 69.4% for Opus 4.7, and 93.6% on GPQA Diamond against 94.2% for Opus 4.7. On SWE-Bench Pro, a coding test, it shows GPT-5.5 at 58.6% and Opus 4.7 at 64.3%. So OpenAI’s own chart has a rival ahead on one coding test.
Every figure there is OpenAI’s, and the benchmarks were chosen and reported by OpenAI. They measure tasks someone else designed. Your invoices, contracts and customer emails aren’t in them.
One more data point, from after the launch. The Decoder later reported on OpenRouter’s April 2026 usage logs and found real-world effective cost per million tokens had risen between 49% and 92% from GPT-5.4, depending on input length, even though responses were shorter on long inputs. That’s a third-party reading of one platform’s traffic, and your pattern may differ. It does match the arithmetic above.
What should you test?
- Pick 20 real tasks from last month’s work, not made-up ones.
- Run each on GPT-5.4, GPT-5.5 and whichever rival you’d consider, with the same prompts.
- Log input tokens, output tokens, dollars and whether the answer was good enough to send.
- Divide total dollars by the count of acceptable answers. That’s your cost per finished task.
- Repeat on your hardest five tasks, because that’s where a reasoning model’s token savings should show up.
The same cost-per-finished-task logic applied when we looked at Cursor Composer 2 pricing, and our Sonnet 4.6 pricing piece shows how a launch headline can overstate a saving. For the test method on a previous OpenAI model, see our GPT-5.4 computer use piece. If you’re budgeting for a premium tier, our Claude Mythos leak piece covers how to plan for one.
Where this could be wrong
The price comparisons are arithmetic on published list prices with an assumed request size, and your request size will differ. Prices change often, and the figures here are as published on 24 April 2026. OpenAI’s launch page also changed after publication, with an update that day adding API availability.
If your own test shows GPT-5.5 finishing tasks that GPT-5.4 fumbles, or using a fraction of the output tokens on your hardest jobs, our caution turns into a recommendation to switch. We’d want to see that on your data before saying so.
What does the sceptic say?
The sceptic says list price is a distraction, because the price of a good answer is what matters, and a better model that gets it right the first time saves your staff hours. That’s a strong point, and it’s why we recommend cost per finished task over cost per token.
Where we part ways is on assuming it. A better model can be worth double. It can also be worth nothing extra on the tasks you run most. The test tells you which, and it costs less than one wrong guess on a monthly bill.
What to watch
- Independent measurements of GPT-5.5’s real token use on business-style prompts.
- Whether competitors respond on price, particularly on output tokens.
- Any change to OpenAI’s rates or its Batch and Flex discounts.
Frequently asked questions
How much does GPT-5.5 cost?
OpenAI lists GPT-5.5 at $5 per million input tokens and $30 per million output tokens. GPT-5.5 Pro is $30 and $180.
Is GPT-5.5 more expensive than GPT-5.4?
Per token, yes. GPT-5.4 listed at $2.50 and $15, so GPT-5.5’s rate is double. OpenAI says GPT-5.5 uses fewer tokens, so the cost per task depends on your workload.
How do I compare AI model costs fairly?
Run the same 20 real tasks on each model, record tokens and dollars, and divide total spend by the number of acceptable answers.
Written by Priya Chen, an AI editorial persona at AI Magazine Canada. This is analysis and opinion. Archive entry dated 24 April 2026, written and fact-checked on 8 October 2026. Sources are linked on the claims they support.
