In this comparison
Overview
GPT-4o and Gemini 2.0 Pro represent the cutting edge of multimodal AI — models that can see, hear, read, and reason across different types of input. OpenAI got there first with GPT-4V, but Google's Gemini has been rapidly catching up and, in some benchmarks, pulling ahead.
The "o" in GPT-4o stands for "omni," and it lives up to the name. Text, images, audio, video — it handles them all with impressive speed. Gemini 2.0 Pro counters with a massive 2M token context window and native Google Search integration that gives it access to real-time information.
This comparison matters because multimodal is where AI is heading. The model that handles mixed inputs best will win the next phase of the AI race.
GPT-4o vs Gemini 2.0 Pro: Side-by-Side
| Category | GPT-4o | Gemini 2.0 Pro |
|---|---|---|
| Developer | OpenAI | Google DeepMind |
| Context Window | 128K tokens | 2M tokens |
| API Input Price | $2.50/M tokens | $1.25/M tokens |
| API Output Price | $10.00/M tokens | $5.00/M tokens |
| Vision | Yes | Yes |
| Audio Input | Yes (native) | Yes (native) |
| Video Understanding | Limited | Yes (native) |
| MMLU Score | 88.7 | 89.5 |
| MATH | 76.6 | 83.7 |
| Speed (tokens/sec) | ~90 | ~75 |
Vision & Image Understanding
Both models can analyze images with impressive accuracy, but they approach it differently. GPT-4o is better at creative interpretation — describing what's happening in a photo, extracting meaning from charts, reading handwriting. Gemini 2.0 Pro is stronger on technical image analysis and can handle higher resolution inputs.
For document processing and OCR, Gemini's got an edge. It handles dense PDFs and scanned documents more reliably. For "tell me what's in this image" style queries, GPT-4o gives more engaging, detailed descriptions.
Winner: Gemini 2.0 Pro for technical vision tasks. GPT-4o for general image understanding.
Context Window & Long Documents
This isn't even close. Gemini 2.0 Pro's 2M token context window dwarfs GPT-4o's 128K. That's roughly 1,500 pages vs 100 pages. If you're working with large codebases, legal documents, or book-length texts, Gemini can ingest the whole thing.
In practice, Gemini maintains quality over long contexts better than most models, though there's still some degradation in the middle sections (the "lost in the middle" problem). GPT-4o handles its 128K window well but you'll hit the limit fast on big projects.
Winner: Gemini 2.0 Pro, decisively.
Reasoning & Problem Solving
GPT-4o is a strong general reasoner, but Gemini 2.0 Pro has pulled ahead on several key benchmarks, particularly MATH and GPQA. Google's deep research integration also means Gemini can ground its reasoning in real data more effectively.
For complex multi-step problems, both are competent. GPT-4o sometimes takes more creative approaches to solutions, while Gemini tends to be more methodical and thorough.
Winner: Gemini 2.0 Pro on benchmarks. Close to a tie in practice.
Speed & Latency
GPT-4o is noticeably faster. The "o" model was specifically optimized for speed, and it shows — responses feel nearly instant for most queries. Gemini 2.0 Pro is no slouch but it's typically 15-20% slower on comparable tasks.
For real-time applications and conversational use, speed matters. GPT-4o's lower latency makes it feel more responsive in chat scenarios.
Winner: GPT-4o.
Pricing & Value
Gemini 2.0 Pro is significantly cheaper on the API. At $1.25/M input tokens vs $2.50/M, you're paying half the price — and getting a 2M context window on top. For high-volume applications, the cost savings add up fast.
Both offer generous free tiers through their consumer products (ChatGPT and Gemini). Google One AI Premium ($20/month) includes Gemini Advanced with 2.0 Pro access, same price as ChatGPT Plus.
Winner: Gemini 2.0 Pro. Better value at every tier.
The Verdict
Gemini 2.0 Pro is the better value and the stronger technical model in 2025. The 2M context window alone is a game-changer for anyone working with large documents, and Google's pricing undercuts OpenAI significantly.
GPT-4o remains the better choice for speed-critical applications and has a more polished conversational feel. Its ecosystem of tools (DALL-E, plugins, GPTs) also gives it an edge for casual users who want everything in one place.
For developers building production applications, Gemini 2.0 Pro's combination of performance, context length, and pricing makes it hard to beat. For everyday chat use, it's closer to a coin flip.
Our pick: Gemini 2.0 Pro for most technical use cases. GPT-4o if speed and ecosystem matter most.
Frequently Asked Questions
Is Gemini 2.0 Pro better than GPT-4o?
On benchmarks, yes — Gemini 2.0 Pro edges ahead on MMLU, MATH, and several other metrics. It also has a much larger context window (2M vs 128K tokens) and costs less. GPT-4o is faster and has a better ecosystem, so 'better' depends on your priorities.
Can both models understand images and video?
Both handle images well. For video, Gemini 2.0 Pro has native video understanding — you can upload clips and ask questions about them. GPT-4o has more limited video capabilities, working primarily through frame extraction.
Which is cheaper for API use?
Gemini 2.0 Pro is about half the price of GPT-4o for API usage. At $1.25/M input tokens vs $2.50/M, plus a much larger context window, it's the clear budget winner for developers.
Which should I use for coding?
Both are strong coders. GPT-4o has a slight edge in generating working code quickly, while Gemini 2.0 Pro's larger context window helps with understanding big codebases. For most coding tasks, the difference is marginal.