o3 Mini vs Qwen2.5-72B-Instruct

On shared benchmark coverage, Google-Proof Q&A has o3 Mini at 79.7 and Qwen2.5-72B-Instruct at 65.4, with o3 Mini ahead by 14.3 points; Chatbot Arena has o3 Mini at 1335 and Qwen2.5-72B-Instruct at 1270, with o3 Mini ahead by 65 points. The largest visible gap is 65 points on Chatbot Arena, 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 differs most on reasoning mode: o3 Mini, function calling: o3 Mini, tool use: o3 Mini, and code execution: o3 Mini. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

For cost, o3 Mini lists $1.1/1M input and $4.4/1M output tokens, while Qwen2.5-72B-Instruct lists $0.12/1M input and $0.39/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen2.5-72B-Instruct lower by about $1.89 per million blended tokens. Availability is 3 providers versus 7, so concentration risk also matters.

Choose o3 Mini when coding workflow support are central to the workload. Choose Qwen2.5-72B-Instruct when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.