Claude Sonnet 4.5 vs GPT-5.2 Codex

On shared benchmark coverage, SWE-bench Verified has Claude Sonnet 4.5 at 77.2 and GPT-5.2 Codex at 72.8, with Claude Sonnet 4.5 ahead by 4.4 points. The largest visible gap is 4.4 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 differs most on code execution: GPT-5.2 Codex. Both models share vision, multimodal input, reasoning mode, and function calling, 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, Claude Sonnet 4.5 lists tiered pricing: 0-200,001t is $3/1M input and $15/1M output; 200,001t+ is $6/1M input and $22.50/1M output, while GPT-5.2 Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GPT-5.2 Codex lower by about $1.17 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 8 providers versus 2, so concentration risk also matters.

Choose Claude Sonnet 4.5 when vision-heavy evaluation and broader provider choice are central to the workload. Choose GPT-5.2 Codex when coding workflow support, larger context windows, 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.