o3 vs Phi-3 Mini 4k

On shared benchmark coverage, Google-Proof Q&A has o3 at 87.7 and Phi-3 Mini 4k at 40.9, with o3 ahead by 46.8 points; HumanEval has o3 at 96.7 and Phi-3 Mini 4k at 59.8, with o3 ahead by 36.9 points. The largest visible gap is 46.8 points on Google-Proof Q&A, 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, structured outputs: o3, and code execution: o3. Both models share the core language-model surface, 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 lists $1/1M input and $4/1M output tokens, while Phi-3 Mini 4k lists $0.05/1M input and $0.25/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi-3 Mini 4k lower by about $1.79 per million blended tokens. Availability is 3 providers versus 4, so concentration risk also matters.

Choose o3 when coding workflow support and larger context windows are central to the workload. Choose Phi-3 Mini 4k 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.