Code Cushman 002 vs GPT-5.4-Cyber
Code Cushman 002 (2021) and GPT-5.4-Cyber (2026) are agentic coding models from OpenAI. Code Cushman 002 ships a not-yet-sourced context window, while GPT-5.4-Cyber ships a not-yet-sourced 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-5.4-Cyber is safer overall; choose Code Cushman 002 when coding workflow support matters.
Specs
| Released | 2021-11-15 | 2026-04-14 |
| Context window | — | — |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | 2025-08 |
Pricing and availability
| Code Cushman 002 | GPT-5.4-Cyber | |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Code Cushman 002 | GPT-5.4-Cyber | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: GPT-5.4-Cyber and reasoning mode: GPT-5.4-Cyber. Both models share the core language-model surface, 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: Code Cushman 002 has no token price sourced yet and GPT-5.4-Cyber 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 Code Cushman 002 when coding workflow support are central to the workload. Choose GPT-5.4-Cyber when reasoning depth 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 Code Cushman 002 or GPT-5.4-Cyber open source?
Code Cushman 002 is listed under Proprietary. GPT-5.4-Cyber 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 multimodal input, Code Cushman 002 or GPT-5.4-Cyber?
GPT-5.4-Cyber 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, Code Cushman 002 or GPT-5.4-Cyber?
GPT-5.4-Cyber 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 Code Cushman 002 over GPT-5.4-Cyber?
GPT-5.4-Cyber is safer overall; choose Code Cushman 002 when coding workflow support matters. If your workload also depends on coding workflow support, start with Code Cushman 002; if it depends on reasoning depth, run the same evaluation with GPT-5.4-Cyber.
Continue comparing
Last reviewed: 2026-04-18. Data sourced from public model cards and provider documentation.