We use essential cookies to keep OpenQiao working. With your permission, optional cookies help us remember your preferences and understand how you use our services. You can accept or reject optional cookies, or manage your choices at any time. Learn more in our Privacy Policy.
gemini-3-pro-preview vs gpt-5.2
Compare gemini-3-pro-preview from google and gpt-5.2 from openai side by side — pricing, context window, features, and provider availability.
gemini-3-pro-preview
Gemini 3 Pro is the next generation in the Gemini series of models, a suite of highly-capable, natively multimodal, reasoning models. Gemini 3 Pro is now Google’s most advanced model for complex tasks, and can comprehend vast datasets, challenging problems from different information sources, including text, audio, images, video, and entire code repositories
gpt-5.2
GPT-5.2 is the newest frontier-grade model in the GPT-5 family, outperforming GPT-5.1 in agentic capabilities and long-context handling. It uses adaptive reasoning to dynamically allocate compute—responding quickly to straightforward questions while applying deeper analysis to more complex tasks. Designed for broad task coverage, GPT-5.2 delivers consistent improvements across math, coding, science, and tool-calling workloads, producing more coherent long-form responses and more reliable tool use.
Model Overview
gemini-3-pro-previewgpt-5.2Access All Top AI Models via OpenQiao
Why limit yourself to one model? OpenQiao gives you access to all leading AI models through a single, unified API. Compare, test, and switch between models effortlessly.
How to use gemini-3-pro-preview or gpt-5.2
Simply change the model name to gemini-3-pro-preview or gpt-5.2 to adjust the model. OpenQiao normalizes requests and responses across providers for you.
from openai import OpenAI
client = OpenAI(
base_url="https://openqiao.com/api/v1",
api_key="<OPENQIAO_API_KEY>",
)
# Chat Completion
completion = client.chat.completions.create(
model="gemini-3-pro-preview",
messages=[
{
"role": "user",
"content": "What is the meaning of life?"
}
]
)
print(completion.choices[0].message.content)
# Responses API
responses = client.responses.create(
model="gemini-3-pro-preview",
input="What is the meaning of life?"
)
print(responses)
