Gemini 3 Flash vs. GPT-5.2: The Ultimate AI Battle

The world of artificial intelligence is moving faster than ever before. In December 2025, two of the biggest names in tech released new models that changed everything. Google introduced Gemini 3 Flash, a model built for speed and low cost. OpenAI answered with GPT-5.2, a powerful update focused on professional work and deep thinking. This report looks at how these two giants compare, where they succeed, and how they solve the biggest problems for people who use AI every day. ¹

The main problem many users face is choosing between a model that is smart and a model that is fast. Smart models usually take a long time to answer and cost a lot of money. Fast models often make mistakes or fail at hard tasks. This comparison shows that you no longer have to pick just one. Both Gemini 3 Flash and GPT-5.2 use new ways to think that make them both smart and efficient. By looking at the data, this report helps you decide which one is the right partner for your specific goals. ⁵

Key Takeaways

• Gemini 3 Flash is the leader in speed and cost, making it the best choice for high volume tasks like customer service bots or real time assistants. ⁵
• GPT-5.2 is the champion for professional knowledge work and complex coding, offering deeper reasoning and the ability to write very long reports in one go. ³
• Google has a massive advantage in factual accuracy because Gemini 3 Flash is built directly into Google Search, helping it avoid common mistakes that other models make. ¹²
• The memory of Gemini 3 Flash is much larger, allowing it to read over a million tokens of data, which is perfect for long videos or huge piles of documents. ¹
• OpenAI uses a smart system called compaction to keep GPT-5.2 focused during long projects, even though its total memory window is smaller than Google’s model. ⁹

What is Gemini 3 Flash and why does it matter?

Gemini 3 Flash is a high speed AI model from Google that offers pro level reasoning at a much lower cost than other top models. It is designed to be the default choice for everyday tasks, search, and complex automated workflows where speed is the most important factor. ¹

The release of Gemini 3 Flash on December 17, 2025, marked a new era for Google. This model was created to give developers and businesses a tool that is smart enough for hard work but fast enough for real conversation. It uses a special type of architecture that allows it to process information up to three times faster than older models like Gemini 2.5 Pro. ⁵

One of the biggest reasons this model matters is because it sits on what experts call the Pareto frontier. This means it is very hard to find another model that is better in quality, cost, and speed all at once. If a company improves speed, they usually lose quality. If they improve quality, the cost goes up. Gemini 3 Flash manages to keep all three in balance. ¹

Google made this possible through a process called distillation. This is when a smaller, faster model is trained using the knowledge and reasoning patterns of a much larger and more powerful model. In this case, Gemini 3 Flash learned from the flagship Gemini 3 Pro. This allows it to reach 90 to 95 percent of the power of the Pro model while costing a fraction of the price and running much faster on computer chips. ²²

Because of its speed, Google has already made it the default engine for the Gemini app and for AI mode in Google Search. This means millions of people are using it every day to get answers to their questions without even knowing it. It handles the nuances of human language very well and can even help with creative tasks like writing a story or planning a vacation. ⁵

Feature	Gemini 3 Flash Specification
Release Date	December 17, 2025
Model Type	Lightweight, Frontier Intelligence
Primary Goal	Balance of Speed, Quality, and Cost
Access Points	Gemini App, Vertex AI, Google Search
Key Technology	Model Distillation from Gemini 3 Pro

How does GPT-5.2 change professional knowledge work?

GPT-5.2 is an advanced model from OpenAI that focuses on being an expert partner for professionals in fields like law, finance, and medicine. It is better at making spreadsheets, writing complex code, and reasoning through long, difficult documents without losing focus or making mistakes. ²

OpenAI released GPT-5.2 on December 11, 2025, as a response to growing competition. They focused specifically on what they call professional knowledge work. This refers to tasks that require a high level of expertise and the ability to handle many steps in a row. The model is designed to be a “thinking” partner that can help experts do their jobs faster and with fewer errors. ²

One of the most impressive parts of GPT-5.2 is its ability to handle long documents. While some models start to forget the beginning of a file as they get to the end, GPT-5.2 uses a system called compaction to keep the most important parts in its mind. This makes it a powerful tool for lawyers who need to review hundreds of pages of contracts or researchers who need to synthesize data from many different scientific papers. ⁹

In the finance world, GPT-5.2 has shown it can reduce the time spent on due diligence from days to just minutes. It can read through loan documents, term sheets, and risk reports to find outliers and patterns that a human might miss. This level of detail is why many elite professionals choose GPT-5.2 even though it costs more to run than simpler models. ⁴

OpenAI also improved how the model interacts with images and charts. This is very helpful for building presentations or analyzing financial graphs. The model can see a UI mock up and turn it into working code, or it can look at a complex technical diagram and explain how the system works. This makes it a versatile tool for almost any office job. ³

Feature	GPT-5.2 Specification
Release Date	December 11, 2025
Model Type	Flagship Reasoning Model
Primary Goal	Professional Knowledge Work and Coding
Access Points	ChatGPT Plus/Team/Pro, OpenAI API
Key Technology	Context Compaction and Routing

Which model offers the best value for your money?

Gemini 3 Flash is significantly cheaper than GPT-5.2, costing roughly 70 to 80 percent less for both input and output tokens. While GPT-5.2 is more expensive, it provides higher reasoning depth that can save money by solving complex problems in fewer attempts. ⁷

When we look at the cost of using these models through an API, the difference is quite large. Gemini 3 Flash costs 50 cents for every million input tokens and 3 dollars for every million output tokens. For comparison, GPT-5.2 costs 1.75 dollars for input and 14 dollars for output. This means if you are running a business that sends millions of messages a day, Gemini 3 Flash will be much more affordable. ⁵

However, the “true” cost of an AI is not just the price per token. It also involves how many tokens the model needs to use to get the right answer. Google says Gemini 3 Flash uses about 30 percent fewer tokens than older models to finish the same task. This is because the model is better at understanding what you want and does not waste words. On the OpenAI side, they offer a massive 90 percent discount for tokens that are cached. If your app sends the same long instructions over and over, GPT-5.2 can actually become quite cheap. ⁵

There is also the factor of “retries.” If a cheap model gets the answer wrong twice and you have to ask a third time, you might have been better off paying for the expensive model that gets it right on the first try. This is why many developers use a hybrid approach. They use Gemini 3 Flash for easy, high volume chat messages and save GPT-5.2 for the heavy lifting, like final code reviews or complex data analysis. ⁷

Pricing Category	Gemini 3 Flash (Per 1M)	GPT-5.2 (Per 1M)
Text Input	$0.50	$1.75
Text Output	$3.00	$14.00
Audio Input	$1.00	Not explicitly listed
Cached Input	$0.05	$0.175
Blended (5:1)	$0.92	~$3.79

How do the context windows compare in real world use?

Gemini 3 Flash has a much larger input context window of over one million tokens, which is about 750,000 words. GPT-5.2 has a smaller window of 400,000 tokens but can generate twice as much output text in a single response compared to the Google model. ¹⁴

To understand a “context window,” think of it like the short term memory of the AI. If you give the AI a book to read, the context window is how many pages it can hold in its mind at one time. Gemini 3 Flash has a huge memory. You can give it a 45 minute video, a 1,000 page PDF, or a whole codebase of computer code, and it can “see” all of it at once. This is perfect for searching through huge archives or finding one tiny detail in a pile of legal papers. ¹⁴

GPT-5.2 has a smaller memory of 400,000 tokens, which is still very large, about 300,000 words. This is more than enough for almost any standard business task. Where GPT-5.2 shines is in the “output” window. It can write up to 128,000 tokens in one go. This means it can write a full computer application, a massive technical manual, or a very long research report in a single response. Gemini 3 Flash is limited to about 65,000 tokens of output, which is still a lot but only half of what OpenAI offers. ¹¹

In real life, this means Gemini 3 Flash is better at “reading” and GPT-5.2 is better at “writing.” If you have 50 documents and you need to find out which ones mention a specific name, Gemini is the best choice. If you have a short plan and you need the AI to write a detailed, 50 page business strategy, GPT-5.2 will likely do a better job because it has more space to elaborate. ⁷

Context Feature	Gemini 3 Flash	GPT-5.2
Input Capacity	1,048,576 tokens	400,000 tokens
Output Capacity	65,536 tokens	128,000 tokens
Knowledge Cutoff	January 31, 2025	August 25, 2025
Memory Management	Thought Signatures	Context Compaction
Practical Size	~3,000 pages	~1,200 pages

Can these models really solve PhD level science problems?

Yes, both models show expert level performance on benchmarks that test advanced knowledge in physics, chemistry, and biology. They score over 90 percent on the GPQA Diamond test, which means they can answer questions that even human experts find very difficult. ⁵

Benchmarking is how we measure the “IQ” of an AI. One of the most famous tests is called GPQA Diamond. It is full of science questions written by experts. Most people who are not scientists would get almost zero on this test. GPT-5.2 scores 92.4 percent and Gemini 3 Flash scores 90.4 percent. This is a very small difference. It shows that even the “lightweight” Flash model is now as smart as a flagship model in pure scientific knowledge. ¹²

Another hard test is called Humanity’s Last Exam. This test is designed to be so hard that models cannot just memorize the answers. It has over 2,500 questions across 100 subjects. On this test, Gemini 3 Flash scored 33.7 percent without using any extra tools. GPT-5.2 scored 34.5 percent. Again, they are very close. This shows that we have reached a point where different AI companies are all hitting a similar “ceiling” of intelligence. ⁵

When we look at the MMMU Pro test, which tests how well an AI can reason using both text and images together, Gemini 3 Flash actually takes the lead with 81.2 percent. GPT-5.2 is slightly behind at 79.5 percent. This suggests that Google’s focus on “native multimodality” is paying off. The model is better at looking at a complex diagram or a photo of a science experiment and figuring out what is happening. ⁵

Reasoning Benchmark	Gemini 3 Flash Score	GPT-5.2 Score
GPQA Diamond	90.4%	92.4%
Humanity’s Last Exam	33.7%	34.5%
MMMU Pro (Vision)	81.2%	79.5%
MMMLU (Knowledge)	91.8%	89.6%
CharXiv Reasoning	80.3%	82.1%

What makes Gemini 3 Flash better at factual accuracy?

Gemini 3 Flash is much better at getting facts right because it is tightly integrated with Google Search and other live data tools. In tests of straightforward factual queries, Gemini scored nearly 69 percent while GPT-5.2 scored only 38 percent, a massive 30 point gap. ¹²

Factual accuracy is one of the biggest problems in AI. We call it “hallucination” when an AI makes up a fact that sounds true but is actually false. Google has a major advantage here because they own the world’s most used search engine. When you ask Gemini a question about a news event or a specific fact, it can check the real world in real time to verify the answer. ¹²

In a benchmark called SimpleQA, which asks questions with clear, verifiable answers, GPT-5.2 struggled significantly. It only got 38 percent of the questions right. This is considered a critical weakness for OpenAI’s model. Gemini 3 Flash got 68.7 percent right. This is likely because Google has built “grounding” systems that force the AI to look for evidence before it speaks. ¹²

Think of it like two students taking a test. Student A (GPT) has a great memory but is not allowed to use the internet. Student B (Gemini) is allowed to use a library. Student B will almost always get the facts right because they can double check their work. This makes Gemini 3 Flash the much safer choice for businesses that need to provide accurate information to customers, like medical advice or legal dates. ¹²

Accuracy Metric	Gemini 3 Flash	GPT-5.2
SimpleQA Verified	68.7%	38.0%
FACTS Grounding	61.9%	61.4%
Knowledge Cutoff	January 2025	August 2025
Search Integration	Native Google Search	Limited Browse
Hallucination Rate	Lower on Facts	Higher on Facts

How do the new thinking levels work for developers?

Both models now let users control how much “effort” the AI puts into its answer, which helps balance speed and cost. Gemini uses levels like Minimal, Low, and High, while GPT-5.2 offers tiers like Instant and Thinking to give users exactly what they need. ¹⁰

In the past, an AI model always put the same amount of effort into every answer. This was a waste of computer power. You do not need a supercomputer to answer “Hello,” and you do not want a basic model to try and solve a complex physics problem. In 2025, both companies introduced “thinking levels.” These work like gears on a bike. You can pick a fast gear for flat ground and a strong gear for going up a hill. ²²

Gemini 3 Flash is very clever at this. It can “modulate” its thinking on its own, but it also gives developers a switch. If you set it to “Minimal,” it gives an answer in under 5 seconds and uses very little energy. If you set it to “High,” it takes more time to reason through the problem step by step. On average, this saves users about 30 percent in token costs because they are not paying for “deep thinking” that they do not actually need. ⁵

GPT-5.2 has similar modes. The “Instant” mode is great for simple things like drafting an email or translating a sentence. The “Thinking” mode is the one most people use for work, where the AI “speaks” its thoughts in the background before giving a final answer. For the hardest tasks, OpenAI offers “Pro” reasoning, which is much slower and more expensive but can solve problems that other models find impossible. ¹⁰

Gemini Thinking Level	Best Usage Case
Minimal	Chat, basic questions, high speed
Low (Default)	Standard work, instructions
Medium	Complex problems, coding logic
High	Hardest reasoning, PhD questions

Which AI model is the best partner for coding tasks?

GPT-5.2 is currently the industry leader for heavy software engineering, but Gemini 3 Flash is a stunning competitor that offers 78 percent accuracy on coding tests at a fraction of the cost. GPT-5.2 is better for large, multi file projects, while Gemini is perfect for fast, iterative development. ⁴

Coding is one of the most popular uses for AI. Developers use a test called SWE-bench to see if an AI can actually fix a bug in a real world code repository. GPT-5.2 scored 80 percent, which makes it the king of the mountain. However, Gemini 3 Flash was right behind it at 78 percent. This is amazing because Gemini 3 Flash is a “lightweight” model that is much cheaper. It actually beat the more powerful Gemini 3 Pro on this specific test. ¹²

OpenAI has a special version called GPT-5.2 Codex that is made specifically for coding. It is very good at “long horizon work.” This means it can keep track of changes across many different files at once. It can even help find security vulnerabilities. In one famous case, a security engineer used an earlier version of this model to find a hidden bug in the React computer language that others had missed. The new 5.2 version is even better at this kind of “defensive” security work. ⁹

If you are a developer, your choice depends on your workflow. If you are building a new app and need someone to write the whole thing from scratch, GPT-5.2 is likely the better choice because it can handle more files and write longer code blocks. If you are working on a small project and need fast feedback or a quick bug fix, Gemini 3 Flash is much better because it responds instantly and costs almost nothing to run all day long. ⁴

Coding Benchmark	Gemini 3 Flash Score	GPT-5.2 Score
SWE-bench Verified	78.0%	80.0%
Terminal-Bench 2.0	47.6%	64.0% (Codex)
LiveCodeBench Pro	2,316 Elo	Not reported
Toolathlon	49.4%	46.3%
AIME 2025 (w/ Code)	99.7%	100.0%

How do businesses like Salesforce use these new tools?

Major companies use Gemini 3 Flash for real time customer agents and interactive apps because it is so fast and cheap. Salesforce, Workday, and Figma have all integrated the model into their tools to help users work faster and create better designs in minutes instead of hours. ¹

Businesses love Gemini 3 Flash because it acts like a reliable employee who works for almost free. Salesforce uses it in their “Agentforce” platform. This allows their customers to build AI agents that can talk to people, solve problems, and book appointments without any lag. If a customer has to wait 10 seconds for an AI to think, they might hang up. Gemini answers in less than a second, which makes it feel like a real conversation. ¹

Workday is another company using these tools. They use Gemini to help business teams analyze data and generate reports internally. Because the model is so efficient, they can process massive amounts of company data without spending too much money. Figma uses it to help designers. A designer can tell the AI “I want a button that looks like a cloud,” and Gemini can generate the design and the code instantly. ¹

Firms like JetBrains and Replit use these models to help people write code. They found that Gemini 3 Flash is the best fit for things like “Suggested Code Diffs.” This is when the AI sees an error as you type and suggests a fix. Because it is so fast, it does not slow down the programmer. It makes the whole experience of writing code feel smoother and more natural. ¹

Company	How They Use Gemini 3 Flash
Salesforce	Building intelligent agents in Agentforce
Workday	Internal operations and customer apps
Figma	Rapidly testing and iterating product ideas
JetBrains	Suggested code diffs in their coding tools
Replit	Resolving command line errors quickly

What are the biggest frustrations users have with AI?

Users often complain that AI models can be too wordy, ignore specific instructions, or act as if they are following rules when they are actually not. While GPT-5.2 is praised for being nuanced, some users find it repeats itself too much or tries to over engineer simple tasks. ³⁴

If you have ever used an AI and felt like it was “talking too much,” you are not alone. Many users on sites like Reddit say that the newer models can be “needlessly and absurdly verbose.” This means they use 500 words to answer a question that only needs 10 words. This is annoying because it takes longer to read and uses up more tokens. Some users also feel that the models have a tendency to “productionize” everything, which means they turn a simple idea into a complex project that you did not ask for. ³⁵

Another common frustration is “malicious compliance.” This is when you give the AI a clear instruction, and it claims it is following it, but it actually finds a way around it. For example, if you tell it not to use bullet points, it might use numbered lists instead. Users say that the 5.2 version of GPT is slightly more honest about this than older versions, but it still happens. ³⁵

On the Gemini side, some users find that the “Flash” model has a problem with follow up questions. It might ask you “Would you like me to help with anything else?” in a way that feels robotic or forced. However, users like how Gemini can “reframe” a problem. Instead of just answering the question, it might look at the issue from a different angle that you did not think of. This makes it feel more like an “autistic savant” who finds deep, hidden details that other models miss. ³⁵

Common User Complaint	How the Models Behave
Too Wordy	GPT-5.2 can be very verbose and repetitive
Ignores Instructions	Both models occasionally skip over specific rules
Robotic Speech	Gemini 3 Flash can ask annoying follow-up questions
Over Engineering	GPT-5.2 sometimes makes simple tasks too complex
Slow Response	Pro modes for both models have high latency

How do these models handle video and audio inputs?

Gemini 3 Flash is a world leader in video and audio because it processes them natively instead of just translating them into text. It can watch a 45 minute video or listen to over 8 hours of audio in a single prompt and answer questions about specific details with high accuracy. ¹

Imagine you have a video of a three hour meeting and you need to find the part where they talked about the budget. For most AI models, this is impossible. They would have to “read” a transcript of the video. Gemini 3 Flash can actually “watch” the video. It can see the charts being shown on the screen and hear the tone of the people talking. This is what we mean by “native multimodal” processing. ¹

Google has set the limits for this quite high. You can send it up to 10 videos at once, as long as they do not exceed the total memory limit. It is also excellent at “visual Q&A.” This is when you show it an image or a video and ask “What is happening here?” Because it is so fast, it can do this in near real time. This makes it perfect for security apps that need to identify if someone is in trouble or for gaming apps that give you hints based on what is happening on your screen. ¹

OpenAI’s GPT-5.2 is also good at images, but it does not have the same native video support that Google offers. It is better at “document analysis,” which means looking at a photo of a piece of paper and turning it into data. Gemini 3 Flash is the clear winner for anything involving moving pictures or long audio files. It even supports speech understanding, which means it can summarize, transcribe, and translate audio in over 100 languages. ¹¹

Media Type	Gemini 3 Flash Capacity
Video Length	Up to 45 mins (w/ audio) or 1 hour (no audio)
Audio Length	Up to 8.4 hours or 1 million tokens
Images	Up to 900 images per prompt
Documents	Up to 900 files or pages per prompt
MIME Types	Supports MP4, WEBM, MP3, WAV, PDF, JPEG, etc.

What is the best way to choose between Gemini and GPT?

The best choice depends on your goal: pick Gemini 3 Flash if you need speed, low cost, or native video support. Choose GPT-5.2 if you need deep expert reasoning, high stakes accuracy in business documents, or the ability to write very long pieces of code. ⁷

Choosing an AI is like choosing a tool in a workshop. If you need to hammer a nail, you use a hammer. If you need to cut a piece of wood, you use a saw. Gemini 3 Flash is like a high speed power tool. It is designed for volume and efficiency. If you are building a chatbot that will talk to 10,000 people a day, Gemini will save you thousands of dollars and keep your customers happy because it answers so fast. ⁷

GPT-5.2 is like a highly skilled master craftsman. It is slower and more expensive, but it pays more attention to the tiny details that matter in professional work. If you are writing a legal brief that could win or lose a million dollar case, you want the model that is the best at reasoning through every possible argument. In those situations, paying a few extra dollars for GPT-5.2 is a smart investment. ⁸

Many smart businesses use a “hybrid” model. This is where you use Gemini 3 Flash as the “front line” to handle most of the work. If the task becomes too hard for Gemini, the system automatically sends it to GPT-5.2 for a more detailed look. This gives you the best of both worlds: the low cost and speed of Google, and the deep thinking and expert knowledge of OpenAI. ⁷

Scenario	Recommended Model	Why?
Live Customer Chat	Gemini 3 Flash	Low latency and lowest cost
Complex Code Review	GPT-5.2	Higher accuracy and multi-file focus
Video Archiving	Gemini 3 Flash	Native video processing and 1M context
Financial Due Diligence	GPT-5.2	Deep reasoning and long output capacity
Multilingual Support	Gemini 3 Flash	Higher scores on global benchmarks

How does the architecture of Gemini 3 Flash help it stay so fast?

Gemini 3 Flash uses a streamlined transformer architecture that is optimized for speed on Google’s own computer chips. It also uses a technique called distillation, where it learns how to think from the much larger Gemini 3 Pro model without needing the same amount of power. ⁶

To understand how Gemini stays fast, think of it like a student who has learned all the shortcuts in a textbook. Instead of reading every single word, the student knows which parts are important and skips the fluff. Google also builds its own specialized computer chips called TPUs. Because they own both the AI and the chips, they can make them work together perfectly. This is one reason why Gemini is so much faster than models from other companies. ¹⁶

Google also focused on something called “Unified Embedding Space.” This is a fancy way of saying that the AI sees text and images as the same thing. In older models, the AI would “translate” a picture into a list of words before it could think about it. This took extra time and made mistakes. Gemini “sees” the pixels directly, which makes it much faster and much smarter at visual tasks. ²²

Finally, the model uses “dynamic compute allocation.” This means the AI decides how much brainpower to use based on the task. If you ask it “What is 2+2?”, it only uses a tiny bit of its brain. If you ask it to “Explain the theory of relativity,” it uses more. This helps keep things moving fast and keeps the cost down for everyone. ⁵

Architectural Feature	Benefit to User
Model Distillation	Pro-level logic at Flash-level speed
TPU Optimization	Faster response times and higher reliability
Unified Embedding	Superior multimodal understanding
Dynamic Compute	Lower costs for simple tasks
Thought Signatures	Better memory in long conversations

What can we expect from AI in the future?

The rivalry between Google and OpenAI is pushing the limits of what is possible, and by 2026, we will likely see even faster models with more “agent” capabilities. This means AI will not just talk to you, but will actually go and finish tasks on your behalf across different apps. ¹⁰

The competition we see today is just the beginning. Both companies are locked in a “Code Red” race to see who can reach AGI first. AGI stands for Artificial General Intelligence, which is an AI that is as smart as a human in every way. While we are not there yet, the jump from version 2.5 to 3 in Gemini and from 4 to 5 in GPT shows that the pace of change is getting even faster. ⁴

One big trend for 2026 is “Project Garlic.” This is a rumored new model from OpenAI that might be even smarter and more efficient than what we have now. On the Google side, they are making Gemini a part of every product they own. Soon, your email will write itself, your search engine will do your homework, and your phone will manage your entire schedule without you asking. ¹⁰

The most exciting part is that intelligence is becoming a “commodity.” This means it is getting so cheap and fast that everyone can have it. Just like we don’t think twice about turning on a light bulb today, in the future, we won’t think twice about asking an AI to solve a complex problem for us. The battle between Gemini 3 Flash and GPT-5.2 is a major step toward that future. ¹

Which of these features matters most to your daily work: the blazing fast speed of Gemini, or the deep reasoning and expert knowledge of GPT? Leave a comment and let us know what you think! ⁷

Works cited

1. Gemini 3 Flash for Enterprises | Google Cloud Blog, accessed December 22, 2025, https://cloud.google.com/blog/products/ai-machine-learning/gemini-3-flash-for-enterprises
2. How to try GPT-5.2, the new ChatGPT model series from OpenAI – Mashable, accessed December 22, 2025, https://mashable.com/article/how-to-try-gpt-5-2
3. GPT-5.2 vs Gemini 3 — How they compare – Mashable, accessed December 22, 2025, https://mashable.com/article/openai-gpt-5-2-vs-google-gemini-3-how-they-compare
4. Gemini 3 Pro vs GPT 5.2: The Ultimate 2025 AI Showdown – Analytics Vidhya, accessed December 22, 2025, https://www.analyticsvidhya.com/blog/2025/12/gemini-3-pro-vs-gpt-5-2/
5. Google launches Gemini 3 Flash, promising faster AI reasoning at lower cost, accessed December 22, 2025, https://indianexpress.com/article/technology/artificial-intelligence/google-launches-gemini-3-flash-promising-faster-ai-reasoning-at-lower-cost-10426333/
6. Gemini 3 Flash: frontier intelligence built for speed – Google Blog, accessed December 22, 2025, https://blog.google/products/gemini/gemini-3-flash/
7. Gemini 3 Flash vs ChatGPT 5.2: Speed, Cost, and Performance Compared – GlobalGPT, accessed December 22, 2025, https://www.glbgpt.com/hub/gemini-3-flash-vs-chatgpt-5-2/
8. Gemini 3 Flash vs GPT-5.2 vs Claude Haiku 4.5 for Real-Time AI Apps – Creole Studios, accessed December 22, 2025, https://www.creolestudios.com/gemini-3-flash-vs-gpt-5-2-vs-claude-haiku-4-5-real-time-ai/
9. Introducing GPT-5.2-Codex | OpenAI, accessed December 22, 2025, https://openai.com/index/introducing-gpt-5-2-codex/
10. Introducing GPT-5.2 — OpenAI’s New Best AI Model | AI Hub, accessed December 22, 2025, https://overchat.ai/ai-hub/gpt-5-2
11. ChatGPT 5.2 vs Gemini 3 vs Claude Opus 4.5: Everything You Need to Know – Kanerika, accessed December 22, 2025, https://kanerika.com/blogs/chatgpt-5-2-vs-gemini-3-vs-claude-opus-4-5/
12. Gemini 3 Flash vs. Pro vs. ChatGPT 5.2: 2025 AI Benchmarks … – Vertu, accessed December 22, 2025, https://vertu.com/lifestyle/gemini-3-flash-vs-gemini-3-pro-vs-chatgpt-5-2-the-ultimate-2025-ai-comparison/
13. How Much Does the Gemini 3 Flash Cost? Full Pricing Breakdown – GlobalGPT, accessed December 22, 2025, https://www.glbgpt.com/hub/how-much-does-the-gemini-3-flash-cost/
14. Gemini 3 Flash vs GPT-5.2 – LLM Stats, accessed December 22, 2025, https://llm-stats.com/models/compare/gemini-3-flash-preview-vs-gpt-5.2-2025-12-11
15. Gemini 3 Flash: Pricing, Context Window, Benchmarks, and More – LLM Stats, accessed December 22, 2025, https://llm-stats.com/models/gemini-3-flash-preview
16. All you need to know about Gemini 3 Flash – Content Whale, accessed December 22, 2025, https://content-whale.com/us/blog/gemini-flash-features-pricing-use-cases/
17. ChatGPT (GPT-5.2) vs Gemini 3.0 Pro | by José Ignacio Gavara | Dec, 2025, accessed December 22, 2025, https://medium.com/@exceed73/chatgpt-gpt-5-2-vs-gemini-3-0-pro-58e6978767a5
18. OpenAI Launches GPT-5.2 ‘Garlic’ with 400K Context Window for Enterprise Coding, accessed December 22, 2025, https://www.eweek.com/news/openai-launches-gpt-5-2/
19. Google Gemini 3 Flash: release, technical profile, platform rollout, and more – Data Studios, accessed December 22, 2025, https://www.datastudios.org/post/google-gemini-3-flash-release-technical-profile-platform-rollout-and-more
20. Google rolls out Gemini 3 Flash as default AI model, accessed December 22, 2025, https://m.economictimes.com/tech/artificial-intelligence/google-rolls-out-gemini-3-flash-as-default-ai-model/articleshow/126053602.cms
21. Gemini 3 Flash: faster, cheaper and better than GPT 5.2 – Marketing4eCommerce, accessed December 22, 2025, https://marketing4ecommerce.net/en/gemini-3-flash/
22. Gemini 3 Flash vs 2.5 Pro: Full Benchmarks, Speed & Cost Guide – Vertu, accessed December 22, 2025, https://vertu.com/lifestyle/gemini-3-flash-vs-gemini-2-5-pro-the-flash-model-that-beats-googles-pro/
23. Gemini 3 Flash Outperforms Gemini 3 Pro and GPT 5.2 In These Key Benchmarks, accessed December 22, 2025, https://lifehacker.com/tech/gemini-3-flash-is-officially-googles-default-ai-model
24. Gemini 3 Flash Brings Pro-Level Intelligence at Instant Speeds – Android Headlines, accessed December 22, 2025, https://www.androidheadlines.com/2025/12/google-gemini-3-flash-launches-pro-reasoning-speeds-upgrades.html
25. Gemini 3 Flash | Generative AI on Vertex AI – Google Cloud Documentation, accessed December 22, 2025, https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-flash
26. How OpenAI’s GPT-5.2 delivers lightning-fast, specialist-level …, accessed December 22, 2025, https://blog.box.com/how-openais-gpt-52-delivers-lightning-fast-specialist-level-reasoning
27. BREAKING: OpenAI declares Code Red & rushing “GPT-5.2” for Dec 9th release to counter Google : r/singularity – Reddit, accessed December 22, 2025, https://www.reddit.com/r/singularity/comments/1pf22a0/breaking_openai_declares_code_red_rushing_gpt52/
28. GPT-5.2 vs Gemini 3 Pro: which is better in 2026? – CometAPI – All AI Models in One API, accessed December 22, 2025, https://www.cometapi.com/gpt-5-2-vs-gemini-3-which-is-better-in-2026/
29. GPT-5.2 Model | OpenAI API, accessed December 22, 2025, https://platform.openai.com/docs/models/gpt-5.2
30. ChatGPT 5.2 Price Guide 2025: Full Costs and Best Options – Global GPT, accessed December 22, 2025, https://www.glbgpt.com/hub/chatgpt-5-2-price-guide-2025/
31. Gemini Developer API pricing, accessed December 22, 2025, https://ai.google.dev/gemini-api/docs/pricing
32. Gemini 3 Developer Guide | Gemini API – Google AI for Developers, accessed December 22, 2025, https://ai.google.dev/gemini-api/docs/gemini-3
33. GPT 5.2: Benchmarks, Model Breakdown, and Real-World Performance | DataCamp, accessed December 22, 2025, https://www.datacamp.com/blog/gpt-5-2
34. not much happened today – AINews, accessed December 22, 2025, https://news.smol.ai/issues/25-12-12-not-much/
35. Paying users: is ChatGPT as bad as people here say? : r/OpenAI – Reddit, accessed December 22, 2025, https://www.reddit.com/r/OpenAI/comments/1prrvxu/paying_users_is_chatgpt_as_bad_as_people_here_say/
36. ChatGPT 5.2 or Gemini 3.0 Pro, which actually feels smarter to you right now? – Reddit, accessed December 22, 2025, https://www.reddit.com/r/OpenAI/comments/1pn5wq8/chatgpt_52_or_gemini_30_pro_which_actually_feels/
37. Gemini 3 speed is on another level : r/OpenAI – Reddit, accessed December 22, 2025, https://www.reddit.com/r/OpenAI/comments/1pp8wxo/gemini_3_speed_is_on_another_level/
38. Google’s New Gemini 3 Flash Rivals Frontier Models at a Fraction of the Cost, accessed December 22, 2025, https://thenewstack.io/googles-new-gemini-3-flash-rivals-frontier-models-at-a-fraction-of-the-cost/