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GPT-4o (11-20) vs o1 (12-17)

GPT-4o (11-20) (2024) and o1 (12-17) (2024) are frontier reasoning models from OpenAI. GPT-4o (11-20) ships a 128K-token context window, while o1 (12-17) ships a 128K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

o1 (12-17) is safer overall; choose GPT-4o (11-20) when coding workflow support matters.

Specs

Specification
Released2024-11-202024-12-17
Context window128K128K
Parameters1.76T (8x222B MoE)*
Architecturemixture of expertsdecoder only
LicenseProprietaryProprietary
Knowledge cutoff2023-10-

Pricing and availability

Pricing attributeGPT-4o (11-20)o1 (12-17)
Input price-$15/1M tokens
Output price-$60/1M tokens
Providers-

Capabilities

CapabilityGPT-4o (11-20)o1 (12-17)
VisionYesNo
MultimodalNoNo
ReasoningNoYes
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionYesYes

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: GPT-4o (11-20) and reasoning mode: o1 (12-17). Both models share 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.

Pricing coverage is uneven: GPT-4o (11-20) has no token price sourced yet and o1 (12-17) has $15/1M input tokens. Provider availability is 0 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose GPT-4o (11-20) when coding workflow support are central to the workload. Choose o1 (12-17) when coding workflow support 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, GPT-4o (11-20) or o1 (12-17)?

GPT-4o (11-20) supports 128K 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.

Is GPT-4o (11-20) or o1 (12-17) open source?

GPT-4o (11-20) is listed under Proprietary. o1 (12-17) 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, GPT-4o (11-20) or o1 (12-17)?

GPT-4o (11-20) 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 reasoning mode, GPT-4o (11-20) or o1 (12-17)?

o1 (12-17) has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for code execution, GPT-4o (11-20) or o1 (12-17)?

Both GPT-4o (11-20) and o1 (12-17) expose code execution. 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.

Where can I run GPT-4o (11-20) and o1 (12-17)?

GPT-4o (11-20) is available on the tracked providers still being sourced. o1 (12-17) is available on Replicate API and OpenAI API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-10. Data sourced from public model cards and provider documentation.