Gemini vs GPT o3: Which AI Wins in 2025?

In the Gemini vs. GPT3 o3 battle, both models are state-of-the-art but serve different needs. This article breaks down how they compare in reasoning, coding, context, multimodal power, cost, and real-world use so you can decide which suits your needs best.

Reasoning & IQ

Gemini 2.5 Pro excels with native chain-of-thought reasoning. It shines in complex, multi-step problems and scores high on benchmarks like MMLU (~85–90%) and GPQA Diamond (~84%). GPT o3 achieves approximately 87.7% on the GPQA Diamond benchmark and takes the lead in early tests like SWE-bench with a score close to 71.7%.

Bottom line:

• Gemini for in-line reasoning.
• o3 When tool use is allowed.

Coding & Software Development

Benchmark tests highlight differences: SWE-bench shows o3 scoring ~71.7%, Gemini around ~63–64%, and Claude Opus tops at ~72.5%.
On code editing tasks, Gemini is strong with multimodal inputs. O3, however, is praised for tool-based workflows and consistent IDE integration.

Quick View:

• O3 leads raw code generation.
• Gemini excels in editing & visual-driven coding.
• Claude Opus 4 remains king if coding alone matters.

Context Window

Gemini 2.5 Pro handles up to 1 million tokens, a huge advantage for massive documents or book-length inputs. OpenAI o3 and other models (o4-mini, Claude) typically top out at 200k tokens.
Takeaway: Gemini is best if you work with super-long inputs.

Multimodal Power

Gemini is built to naturally understand and process text, images, audio, and video content. OpenAI’s o3 is also multimodal, but Gemini leads in depth, especially with video and audio.

Pricing & Access

Gemini integrates into Google AI tools, with free and paid tiers via Gemini Advanced or Google One. o3 can be accessed by ChatGPT Plus or Pro users and is also offered via API, usually costing around $10 per million input tokens.

Quick Price Table

Pros and Cons – Gemini vs GPT o3

Google Gemini – Pros and Cons

Pros:

• Huge context window (up to 1 million tokens), great for long documents and memory.
• Advanced multimodal support handles text, images, audio, and video natively.
• Deep reasoning excels in logic-heavy tasks and chain-of-thought answers.
• Tight integration with Google tools, works well with Gmail, Docs, Sheets, etc.
• Free access available, generous free tier for casual users.

Cons:

• Not as strong in real-time code generation as GPT-3.
• Limited external tool usage, mainly designed for Google’s own ecosystem.
• Slightly slower response times under heavy load (depending on usage).

OpenAI GPT-3 – Pros and Cons

Pros:

• Excellent at tool use, great for data analysis, coding, and problem-solving.
• Strong performance in coding, higher accuracy on software benchmarks.
• Fast and smooth user experience, especially in ChatGPT Plus.
• Multimodal abilities support text, image, and voice input/output.
• Stable and widely used, trusted by developers, writers, and businesses.

Cons:

• Context window is smaller (up to 128K–200K tokens max).
• No free tier for O3, you must pay to access it.
• Limited visual/video understanding compared to Gemini.

Comparison Summary

Which One Suits You?

Choose Gemini when:

• You need to process long documents.
• Your tasks involve images, audio, or video.
• You already use Google tools and workflows.

Choose O3 when:

• You rely on code generation and IDE integration.
• You need tool-augmented math or debugging.
• You use ChatGPT Pro or OpenAI APIs.

Use both. Many users combine them: Gemini for deep research and massive input handling, and o3 for hands-on coding or interactive workflows.

Which Is the Best AI in 2025?

Conclusion

In the Gemini vs. GPT-3 showdown, there’s no absolute winner. Gemini dominates long-context and multimodal tasks, while o3 excels in coding, tool usage, and IDE support. Decide based on your needs, or better yet, use both and let them do what they do best.