Gemini 2.5 Pro vs o3

On shared benchmark coverage, SWE-bench Verified has Gemini 2.5 Pro at 63.8 and o3 at 71.7, with o3 ahead by 7.9 points; AIME 2024 has Gemini 2.5 Pro at 92 and o3 at 96.7, with o3 ahead by 4.7 points; Google-Proof Q&A has Gemini 2.5 Pro at 86.4 and o3 at 87.7, with o3 ahead by 1.3 points. The largest visible gap is 7.9 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint is close: both models cover vision, multimodal input, reasoning mode, function calling, and tool use. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

For cost, Gemini 2.5 Pro lists tiered pricing: <=200k tokens is $1.25/1M input and $10/1M output; 0-200,001t is $1.25/1M input and $10/1M output; >200k tokens is $2.50/1M input and $15/1M output; 200,001t+ is $2.50/1M input and $15/1M output, while o3 lists $2/1M input and $8/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts o3 lower by about $0.08 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 4 providers versus 3, so concentration risk also matters.

Choose Gemini 2.5 Pro when coding workflow support, larger context windows, and lower cheapest-tier input-token cost are central to the workload. Choose o3 when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.