GPT-4o (11-20) vs o3 Deep Research
GPT-4o (11-20) (2024) and o3 Deep Research (2026) are frontier reasoning models from OpenAI. GPT-4o (11-20) ships a 128K-token context window, while o3 Deep Research ships a 200K-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.
o3 Deep Research is safer overall; choose GPT-4o (11-20) when coding workflow support matters.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-11-20 | 2026-01-01 |
| Context window | 128K | 200K |
| Parameters | 1.76T (8x222B MoE)* | — |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2023-10 | - |
Pricing and availability
| Pricing attribute | GPT-4o (11-20) | o3 Deep Research |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | GPT-4o (11-20) | o3 Deep Research |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | No | Yes |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: o3 Deep Research, reasoning mode: o3 Deep Research, function calling: o3 Deep Research, tool use: o3 Deep Research, structured outputs: o3 Deep Research, and code execution: GPT-4o (11-20). Both models share vision, 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 o3 Deep Research has no token price sourced yet. Provider availability is 0 tracked routes versus 0. 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 o3 Deep Research when reasoning depth and larger context windows 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.
FAQ
Which has a larger context window, GPT-4o (11-20) or o3 Deep Research?
o3 Deep Research supports 200K tokens, while GPT-4o (11-20) 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 o3 Deep Research open source?
GPT-4o (11-20) is listed under Proprietary. o3 Deep Research 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 o3 Deep Research?
Both GPT-4o (11-20) and o3 Deep Research expose vision. 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 multimodal input, GPT-4o (11-20) or o3 Deep Research?
o3 Deep Research 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.
Which is better for reasoning mode, GPT-4o (11-20) or o3 Deep Research?
o3 Deep Research 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.
When should I pick GPT-4o (11-20) over o3 Deep Research?
o3 Deep Research is safer overall; choose GPT-4o (11-20) when coding workflow support matters. If your workload also depends on coding workflow support, start with GPT-4o (11-20); if it depends on reasoning depth, run the same evaluation with o3 Deep Research.
Continue comparing
Last reviewed: 2026-04-27. Data sourced from public model cards and provider documentation.