GPT-5.5-Cyber vs o3 Deep Research
GPT-5.5-Cyber (2026) and o3 Deep Research (2026) are frontier-tier reasoning models from OpenAI. GPT-5.5-Cyber ships a not-yet-sourced 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.
GPT-5.5-Cyber is safer overall; choose o3 Deep Research when vision-heavy evaluation matters.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-30 | 2026-01-01 |
| Context window | — | 200K |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | GPT-5.5-Cyber | o3 Deep Research |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | GPT-5.5-Cyber | o3 Deep Research |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: o3 Deep Research, tool use: o3 Deep Research, and structured outputs: o3 Deep Research. Both models share vision, multimodal input, and reasoning mode, 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-5.5-Cyber 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-5.5-Cyber when vision-heavy evaluation are central to the workload. Choose o3 Deep Research when vision-heavy evaluation 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
Is GPT-5.5-Cyber or o3 Deep Research open source?
GPT-5.5-Cyber 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-5.5-Cyber or o3 Deep Research?
Both GPT-5.5-Cyber 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-5.5-Cyber or o3 Deep Research?
Both GPT-5.5-Cyber and o3 Deep Research expose multimodal input. 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 reasoning mode, GPT-5.5-Cyber or o3 Deep Research?
Both GPT-5.5-Cyber and o3 Deep Research 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 function calling, GPT-5.5-Cyber or o3 Deep Research?
o3 Deep Research has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
When should I pick GPT-5.5-Cyber over o3 Deep Research?
GPT-5.5-Cyber is safer overall; choose o3 Deep Research when vision-heavy evaluation matters. If your workload also depends on vision-heavy evaluation, start with GPT-5.5-Cyber; if it depends on vision-heavy evaluation, run the same evaluation with o3 Deep Research.
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Last reviewed: 2026-05-05. Data sourced from public model cards and provider documentation.