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GPT-5.2

11th December 2025

OpenAI reportedly declared a “code red” on the 1st of December in response to increasingly credible competition from the likes of Google’s Gemini 3. It’s less than two weeks later and they just announced GPT-5.2, calling it “the most capable model series yet for professional knowledge work”.

Key characteristics of GPT-5.2

The new model comes in two variants: GPT-5.2 and GPT-5.2 Pro. There’s no Mini variant yet.

GPT-5.2 is available via their UI in both “instant” and “thinking” modes, presumably still corresponding to the API concept of different reasoning effort levels.

The knowledge cut-off date for both variants is now August 31st 2025. This is significant—GPT 5.1 and 5 were both Sep 30, 2024 and GPT-5 mini was May 31, 2024.

Both of the 5.2 models have a 400,000 token context window and 128,000 max output tokens—no different from 5.1 or 5.

Pricing wise 5.2 is a rare increase—it’s 1.4x the cost of GPT 5.1, at $1.75/million input and $14/million output. GPT-5.2 Pro is $21.00/million input and a hefty $168.00/million output, putting it up there with their previous most expensive models o1 Pro and GPT-4.5.

So far the main benchmark results we have are self-reported by OpenAI. The most interesting ones are a 70.9% score on their GDPval “Knowledge work tasks” benchmark (GPT-5 got 38.8%) and a 52.9% on ARC-AGI-2 (up from 17.6% for GPT-5.1 Thinking).

The ARC Prize Twitter account provided this interesting note on the efficiency gains for GPT-5.2 Pro

A year ago, we verified a preview of an unreleased version of @OpenAI o3 (High) that scored 88% on ARC-AGI-1 at est. $4.5k/task

Today, we’ve verified a new GPT-5.2 Pro (X-High) SOTA score of 90.5% at $11.64/task

This represents a ~390X efficiency improvement in one year

GPT-5.2 can be accessed in OpenAI’s Codex CLI tool like this:

codex -m gpt-5.2

There are three new API models:

OpenAI have published a new GPT-5.2 Prompting Guide.

It’s better at vision

One note from the announcement that caught my eye:

GPT‑5.2 Thinking is our strongest vision model yet, cutting error rates roughly in half on chart reasoning and software interface understanding.

I had dissapointing results from GPT-5 on an OCR task a while ago. I tried it against GPT-5.2 and it did much better:

llm -m gpt-5.2 ocr -a https://static.simonwillison.net/static/2025/ft.jpeg

Here’s the result from that, which cost 1,520 input and 1,022 for a total of 1.6968 cents.

Rendering some pelicans

For my classic “Generate an SVG of a pelican riding a bicycle” test:

llm -m gpt-5.2 "Generate an SVG of a pelican riding a bicycle"

Described by GPT-5.2: Cartoon-style illustration: A white, duck-like bird with a small black eye, oversized orange beak (with a pale blue highlight along the lower edge), and a pink neckerchief rides a blue-framed bicycle in side view; the bike has two large black wheels with gray spokes, a blue front fork, visible black crank/pedal area, and thin black handlebar lines, with gray motion streaks and a soft gray shadow under the bike on a light-gray road; background is a pale blue sky with a simple yellow sun at upper left and two rounded white clouds (one near upper center-left and one near upper right).

And for the more advanced alternative test, which tests instruction following in a little more depth:

llm -m gpt-5.2 "Generate an SVG of a California brown pelican riding a bicycle. The bicycle
must have spokes and a correctly shaped bicycle frame. The pelican must have its
characteristic large pouch, and there should be a clear indication of feathers.
The pelican must be clearly pedaling the bicycle. The image should show the full
breeding plumage of the California brown pelican."

Digital illustration on a light gray/white background with a thin horizontal baseline: a stylized California brown pelican in breeding plumage is drawn side-on, leaning forward and pedaling a bicycle; the pelican has a dark brown body with layered wing lines, a pale cream head with a darker brown cap and neck shading, a small black eye, and an oversized long golden-yellow bill extending far past the front wheel; one brown leg reaches down to a pedal while the other is tucked back; the bike is shown in profile with two large spoked wheels (black tires, white rims), a dark frame, crank and chainring near the rear wheel, a black saddle above the rear, and the front fork aligned under the pelican’s head; text at the top reads "California brown pelican (breeding plumage) pedaling a bicycle".

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This is GPT-5.2 by Simon Willison, posted on 11th December 2025.

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