LLM Reference

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, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

o3 is ~650% cheaper at $2/1M; pay for o1 (12-17) only for coding workflow support.

Decision scorecard

Local evidence first
Signalo1 (12-17)o3
Best forreasoning-heavy apps and provider-routed productionreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitCoding, Agents, and Long contextCoding, RAG, and Agents
Context window128k200k
Cheapest output$60/1M tokens$8/1M tokens
Provider routes2 tracked3 tracked
Shared benchmarks3 rowsGoogle-Proof Q&A leader

Decision tradeoffs

Choose o1 (12-17) when...
  • Local decision data tags o1 (12-17) for Coding, Agents, and Long context.
Choose o3 when...
  • o3 leads the largest shared benchmark signal on Google-Proof Q&A by 9.7 points.
  • o3 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • o3 has the lower cheapest tracked output price at $8/1M tokens.
  • o3 has broader tracked provider coverage for fallback and procurement flexibility.
  • o3 uniquely exposes Vision, Multimodal, and Function calling in local model data.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Lower estimate o3

o1 (12-17)

$27,000

Cheapest tracked route/tier: Replicate API

o3

$3,600

Cheapest tracked route/tier: OpenAI API

Estimated monthly gap: $23,400. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

o1 (12-17) -> o3
  • Provider overlap exists on OpenAI API; start route-level A/B tests there.
  • o3 is $52/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • o3 adds Vision, Multimodal, and Function calling in local capability data.
o3 -> o1 (12-17)
  • Provider overlap exists on OpenAI API; start route-level A/B tests there.
  • o1 (12-17) is $52/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.

Specs

Specification
Released2024-12-172025-04-16
Context window128k200k
Parameters
Architecturedecoder onlydecoder only
LicenseProprietaryProprietary
Knowledge cutoff-2024-06

Pricing and availability

Pricing attributeo1 (12-17)o3
Input price$15/1M tokens$2/1M tokens
Output price$60/1M tokens$8/1M tokens
Providers

Capabilities

Capabilityo1 (12-17)o3
VisionNoYes
MultimodalNoYes
ReasoningYesYes
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionYesYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

Benchmarko1 (12-17)o3
Google-Proof Q&A78.087.7
Chatbot Arena1385.01412.0
Massive Multi-discipline Multimodal Understanding78.282.9

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 vision: o3, multimodal input: o3, function calling: o3, tool use: o3, and 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 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 $24.70 per million blended tokens. Availability is 2 providers versus 3, 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 vision, o1 (12-17) or o3?

o3 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, o1 (12-17) or o3?

o3 has the clearer documented multimodal input signal in this comparison. If multimodal input 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, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-29. Data sourced from public model cards and provider documentation.