Claude 3.7 Sonnet vs o3

On shared benchmark coverage, SWE-bench Verified has Claude 3.7 Sonnet at 70.3 and o3 at 71.7, with o3 ahead by 1.4 points; LiveCodeBench has Claude 3.7 Sonnet at 68.9 and o3 at 85.5, with o3 ahead by 16.6 points; Massive Multi-discipline Multimodal Understanding has Claude 3.7 Sonnet at 75 and o3 at 82.9, with o3 ahead by 7.9 points. The largest visible gap is 16.6 points on LiveCodeBench, 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, Claude 3.7 Sonnet lists $3/1M input and $15/1M output tokens on the cheapest tracked provider, 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 $2.80 per million blended tokens. Availability is 6 providers versus 3, so concentration risk also matters.

Choose Claude 3.7 Sonnet when coding workflow support and broader provider choice are central to the workload. Choose o3 when coding workflow support and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.