Is GPT-4o or GPT-5.6 Terra cheaper?

GPT-5.6 Terra is cheaper on input — $2.00 per million against $2.50, a difference of 1.3x. Output rates differ separately, and a workload heavy on generated text can reverse which one costs less overall.

Which has the larger context window?

GPT-5.6 Terra, at 1,050,000 tokens against 128,000.

Can I compare them on my own prompt?

Yes. The calculator counts any text against every model at once, so you can see both figures for your actual workload rather than for a generic example.

GPT-4o vs GPT-5.6 Terra

Whether moving to the current generation is cheaper as well as newer.

Side by side

Attribute	GPT-4o	GPT-5.6 Terra
Input, per 1M tokens	$2.50	$2.00
Output, per 1M tokens	$10.00	$12.00
Context window	128,000	1,050,000
Provider	OpenAI	OpenAI
Tokenizer	o200k_base	o200k_base
Long-context tier	none	above 272,000
Retires	no date announced	no date announced

Which to choose

On cost, GPT-5.6 Terra is 1.3x cheaper per million input tokens. On a workload that reads far more than it writes, that ratio is close to the whole difference in the bill.
On capacity, GPT-5.6 Terra holds more in one request. That matters only if you are near the smaller ceiling — below it, the extra room changes nothing.
On long prompts, at least one of these bills the entire request at an elevated rate past a threshold. A comparison made on short prompts can invert once you cross it.

What this page does not tell you. Which model produces better answers. That depends on your task, and this site has no benchmark data — everything above is drawn from published pricing and specifications. Compare quality by running your own prompts through both.

Count your prompt on both GPT-4o details GPT-5.6 Terra details

Common questions

Is GPT-4o or GPT-5.6 Terra cheaper?: GPT-5.6 Terra is cheaper on input — $2.00 per million against $2.50, a difference of 1.3x. Output rates differ separately, and a workload heavy on generated text can reverse which one costs less overall.
Which has the larger context window?: GPT-5.6 Terra, at 1,050,000 tokens against 128,000.
Can I compare them on my own prompt?: Yes. The calculator counts any text against every model at once, so you can see both figures for your actual workload rather than for a generic example.