Two flagships of late 2025
The last weeks of 2025 were rich in high-profile releases. OpenAI released OpenAI GPT-5.2 on December 11, just a month after Google Gemini 3 Pro appeared (November 19). Previously, OpenAI used to keep longer pauses, but this time it had to act fast: Gemini 3 Pro instantly took the top spot in hype and drew users' attention. In effect, GPT-5.2 became the answer to that success.
Importantly, the models approach tasks from different angles. GPT-5.2 offers three modes — Instant for quick responses, Thinking for deep reasoning, and Pro for maximum power. Google Gemini 3 Pro works as a single general-purpose multimodal model, without fine-tuning for a specific scenario. These are fundamentally different philosophies.
Context and multimodality
Perhaps the most obvious difference is the context window size. OpenAI GPT-5.2 reaches 400K tokens. That is, for example, roughly three novels the size of "War and Peace" — more than enough for the vast majority of everyday tasks. But Google Gemini 3 Pro goes further: up to 1M tokens. In practice, this means Gemini can simultaneously "hold in its head" an entire technical repository, multi-volume documentation, or several hours of video material.
The models diverge even more when it comes to multimodality. GPT-5.2 accepts text and images as input, but its output is almost always text. Video and audio are either not a primary scenario for it, or require separate tools. Gemini 3 Pro is built differently: it is multimodal from the ground up and can work with all four data types — text, images, sound, and video — both as input and as output. That is a significant advantage for anyone who does not want to assemble a pipeline from multiple models.
Use cases
Because of these differences, the models have ended up with different "professions." OpenAI GPT-5.2 is most confident where thinking is required: complex multi-step reasoning, drafting professional texts, software development, data analysis, and scientific calculations. It is a tool for those who put result quality above universality.
Google Gemini 3 Pro, by contrast, excels in scenarios with long context and mixed data types. You can feed it research PDFs, video interviews, and audio recordings all at once, and ask for a summary. Plus, Gemini is deeply integrated into the Google ecosystem: Workspace, Search, and other services. If your work is tied to Google tools, this gives you a serious edge.
API and pricing
For developers, the key question is the API. OpenAI GPT-5.2 has mature infrastructure with several endpoints: chat, responses, realtime, and assistant. Over the past couple of years, it has become the de facto standard, so moving existing code to the new model is usually straightforward. Google Gemini 3 Pro is distributed via the Gemini API, available in Google Cloud and Vertex AI. That is also convenient, but if your project is built around OpenAI, the switch will take time.
Prices differ noticeably, though. GPT-5.2 charges about $1.75 per million input tokens and around $14 per million output tokens. Moreover, tokens spent on "reasoning" are billed as output — which can unexpectedly inflate the bill on complex tasks. Gemini 3 Pro in preview is cheaper: about $1 per million input tokens and $6 per million output tokens. This is a starting price, though, and it may vary depending on plan and region. For large volumes, the difference is substantial.
Answer quality and benchmarks
OpenAI positions OpenAI GPT-5.2 as the most intelligent general-purpose model on the market. And judging by the benchmarks, this is not just marketing: GPT-5.2 outperforms competitors in nearly every evaluated category. Its results are especially strong in tasks involving logic, generalization, and solving unfamiliar examples — exactly the kind where a model cannot simply memorize an answer from training data. GPT-5.2 also has a noticeable edge over Google Gemini 3 Pro in general knowledge coverage.
Users confirm this picture. Many industry experts in professional and knowledge-intensive fields say they prefer GPT-5.2's answers. This does not mean Gemini is weak — it is strong in multimodal and long-context tasks. But when it comes to deep reasoning and precision of phrasing, the community is still leaning toward OpenAI.
So what should you choose?
The answer depends on your task. If you write code, do research, or prepare complex analytical materials where logic matters, take a closer look at OpenAI GPT-5.2. You will pay more for the API, but you will get a maximally "thinking" model that rarely errs in reasoning.
If you need to process long documents, work with audio and video, and interact closely with Google services, then Google Gemini 3 Pro is the more logical choice. Its 1M context and native multimodality open up scenarios that GPT-5.2 currently covers only partially — and at a lower price.
Or you can simply not choose. By the end of 2025, many teams use both models, switching between them depending on the task type. That is flexible and removes the "what's better" question: the better model is the one that solves your particular problem.
