If you have been following AI this year, you have probably seen two claims flying around at the same time:
Gemini 3 is the new best model
GPT-5.2 is the most useful model for real work
Both can be true, depending on what you are trying to do. This blog compares Gemini 3 and GPT-5.2 using what the companies themselves publish, plus what matters in real use: reasoning, coding, long-context work, multimodal skills, tools, pricing, and practical fit.
Quick Takeaways
If you want the biggest context window and strong multimodal input (including audio and video), Gemini 3 stands out.
If you want a very strong general work model with great long-document accuracy, strong coding, and a mature tools ecosystem, GPT-5.2 is hard to beat.
“Best model” depends on the job. The smart choice is picking the one that matches your workflow, budget, and product stack.
What These Models Are Trying To Be Good At?
Gemini 3 (Google)
Gemini 3 is positioned as a top multimodal reasoning model with a very large context window and strong performance in both “thinking” tasks and developer tasks. Google also talks a lot about agent-style workflows and coding experiences around Gemini 3 (Studio, CLI, and newer developer platforms).
GPT-5.2 (OpenAI)
GPT-5.2 is positioned as a flagship model series for professional knowledge work, long-running agent workflows, coding, and tool use. OpenAI also splits the experience into variants like Instant, Thinking, and Pro, so the same family can behave differently depending on how much “thinking time” you want it to spend.
Headline Performance: What The Published Benchmark Numbers Say
Benchmarks are not the full story, but they help when you read them carefully:
Different orgs use different prompts, settings, and rules
Some tests allow tools, some do not
“One score” never predicts your exact use case
Still, here is what the official posts highlight.
Reasoning And Academic-Style Tests
Google reports Gemini 3 Pro doing very well on:
LMArena leaderboard score: 1501 Elo
Humanity’s Last Exam (no tools): 37.5%
GPQA Diamond (no tools): 91.9%
Google also reports a separate mode, Gemini 3 Deep Think, doing even higher on some of these:Humanity’s Last Exam (no tools): 41.0%
GPQA Diamond (no tools): 93.8%
OpenAI reports GPT-5.2 Thinking doing very well on:
GPQA Diamond (no tools): 92.4%
Humanity’s Last Exam (no tools): 34.5%
AIME 2025 (no tools): 100.0%
ARC-AGI-2 (Verified): 52.9% (and GPT-5.2 Pro higher)
Practical read:
Gemini 3 Pro and GPT-5.2 Thinking are both extremely strong on hard reasoning tests.
Gemini 3 Deep Think looks especially strong, but it is presented as a separate mode with limited availability.
GPT-5.2 has strong “work style” evaluations too, not just academic tests.
Coding And Software Engineering
Google reports Gemini 3 Pro performance highlights like:
SWE-bench Verified: 76.2%
Terminal-Bench 2.0: 54.2%
WebDev Arena: 1487 Elo
OpenAI reports GPT-5.2 Thinking highlights like:
SWE-bench Verified: 80.0%
SWE-Bench Pro (Public): 55.6% (a broader, multi-language style eval)
Practical read:
Both are top-tier coding models.
GPT-5.2 looks slightly ahead on SWE-bench Verified in the official numbers.
Gemini 3 shows strong results on developer experience style leaderboards too.
Long Context: Who Handles Big Inputs Better?
This is one of the clearest “apples to apples” differences. Gemini 3 wins over ChatGPT 5.2 via a big margin.
Gemini 3 is promoted with a 1 million token context window.
GPT-5.2 is published with a 400,000 token context window and up to 128,000 output tokens.
Multimodal: Text, Images, Audio, Video
Gemini 3 is positioned as deeply multimodal. Google’s post talks about handling text, images, video, and audio, and the pricing tables for Gemini 3 inputs include audio and video. GPT-5.2 supports text and image input, and OpenAI’s model page clearly separates what is supported.
Practical read:
If your product needs audio or video as first-class input (call center clips, voice notes, lecture videos), Gemini 3 is the more direct fit.
If your product is mostly text, plus occasional screenshots or images, GPT-5.2 covers that well.
Tool Use And Agents: Who Feels Better In Real Work?
This is the hardest part to judge from “scores,” because tools are a product ecosystem topic, not just a model topic.
OpenAI is very explicit that GPT-5.2 is designed for tool calling and multi-step projects, and it is integrated into APIs built for tool use.
Google is also pushing agent workflows and developer tooling around Gemini 3, including first-party experiences that aim to make agent-style building easier.
Which One Should You Choose?
Pick Gemini 3 if:
You need multimodal input beyond images, especially audio and video
You want the biggest context window for “one prompt with everything”
Your stack is Google-first and you want tight integration with Google tooling
Pick GPT-5.2 if:
You want a strong all-rounder for professional work, coding, and long projects
You care about long-context accuracy, not only long-context size
You want a mature tools ecosystem and clear developer docs for agent workflows
The honest answer is that many serious teams will use both:
Gemini 3 for heavy multimodal intake and very large context jobs
GPT-5.2 for day-to-day “work model” tasks, coding, tools, and production workflows
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