o1 (12-17) vs o3
o1 (12-17) (2024) and o3 (2025) are frontier-tier reasoning models from OpenAI. o1 (12-17) ships a 128K-token context window, while o3 ships a 200K-token context window. On Google-Proof Q&A, o3 leads by 9.7 pts. On pricing, o3 costs $2/1M input tokens versus $15/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
o3 is ~650% cheaper at $2/1M; pay for o1 (12-17) only for coding workflow support.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-12-17 | 2025-03-31 |
| Context window | 128K | 200K |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | o1 (12-17) | o3 |
|---|---|---|
| Input price | $15/1M tokens | $2/1M tokens |
| Output price | $60/1M tokens | $8/1M tokens |
| Providers |
Capabilities
| Capability | o1 (12-17) | o3 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | Yes |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | Yes | Yes |
Benchmarks
| Benchmark | o1 (12-17) | o3 |
|---|---|---|
| Google-Proof Q&A | 78.0 | 87.7 |
| Chatbot Arena | 1385.0 | 1412.0 |
| Massive Multi-discipline Multimodal Understanding | 78.2 | 82.9 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has o1 (12-17) at 78 and o3 at 87.7, with o3 ahead by 9.7 points; Chatbot Arena has o1 (12-17) at 1385 and o3 at 1412, with o3 ahead by 27 points; Massive Multi-discipline Multimodal Understanding has o1 (12-17) at 78.2 and o3 at 82.9, with o3 ahead by 4.7 points. The largest visible gap is 27 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 structured outputs: o3. Both models share reasoning mode and code execution, 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, o1 (12-17) lists $15/1M input and $60/1M output tokens, 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 $24.70 per million blended tokens. Availability is 2 providers versus 2, so concentration risk also matters.
Choose o1 (12-17) when coding workflow support are central to the workload. Choose o3 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.
FAQ
Which has a larger context window, o1 (12-17) or o3?
o3 supports 200K tokens, while o1 (12-17) supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, o1 (12-17) or o3?
o3 is cheaper on tracked token pricing. o1 (12-17) costs $15/1M input and $60/1M output tokens. o3 costs $2/1M input and $8/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is o1 (12-17) or o3 open source?
o1 (12-17) is listed under Proprietary. o3 is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for reasoning mode, o1 (12-17) or o3?
Both o1 (12-17) and o3 expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for structured outputs, o1 (12-17) or o3?
o3 has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run o1 (12-17) and o3?
o1 (12-17) is available on Replicate API and OpenAI API. o3 is available on OpenAI API and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.