Nano Banana Pro (Gemini 3 Pro Image Preview) vs GPT-5.4-Cyber
Nano Banana Pro (Gemini 3 Pro Image Preview) (2025) and GPT-5.4-Cyber (2026) are frontier reasoning models from Google DeepMind and OpenAI. Nano Banana Pro (Gemini 3 Pro Image Preview) ships a 66K-token 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.
GPT-5.4-Cyber is safer overall; choose Nano Banana Pro (Gemini 3 Pro Image Preview) when provider fit matters.
Decision scorecard
Local evidence first| Signal | Nano Banana Pro (Gemini 3 Pro Image Preview) | GPT-5.4-Cyber |
|---|---|---|
| Decision fit | General | Vision |
| Context window | 66K | — |
| Cheapest output | $120/1M tokens | - |
| Provider routes | 3 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Nano Banana Pro (Gemini 3 Pro Image Preview) has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Nano Banana Pro (Gemini 3 Pro Image Preview) has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.4-Cyber uniquely exposes Multimodal and Reasoning in local model data.
- Local decision data tags GPT-5.4-Cyber for Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Nano Banana Pro (Gemini 3 Pro Image Preview)
$31,600
Cheapest tracked route: Google AI Studio
GPT-5.4-Cyber
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Nano Banana Pro (Gemini 3 Pro Image Preview) and GPT-5.4-Cyber; plan for SDK, billing, or endpoint changes.
- GPT-5.4-Cyber adds Multimodal and Reasoning in local capability data.
- No overlapping tracked provider route is sourced for GPT-5.4-Cyber and Nano Banana Pro (Gemini 3 Pro Image Preview); plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Multimodal and Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-01 | 2026-04-14 |
| Context window | 66K | — |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Unknown | Proprietary |
| Knowledge cutoff | - | 2025-08 |
Pricing and availability
| Pricing attribute | Nano Banana Pro (Gemini 3 Pro Image Preview) | GPT-5.4-Cyber |
|---|---|---|
| Input price | $2/1M tokens | - |
| Output price | $120/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Nano Banana Pro (Gemini 3 Pro Image Preview) | GPT-5.4-Cyber |
|---|---|---|
| Vision | No | No |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
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: Nano Banana Pro (Gemini 3 Pro Image Preview) has $2/1M input tokens and GPT-5.4-Cyber has no token price sourced yet. Provider availability is 3 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Nano Banana Pro (Gemini 3 Pro Image Preview) when provider fit and broader provider choice 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 Nano Banana Pro (Gemini 3 Pro Image Preview) or GPT-5.4-Cyber open source?
Nano Banana Pro (Gemini 3 Pro Image Preview) is listed under Unknown. 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, Nano Banana Pro (Gemini 3 Pro Image Preview) 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, Nano Banana Pro (Gemini 3 Pro Image Preview) 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.
Where can I run Nano Banana Pro (Gemini 3 Pro Image Preview) and GPT-5.4-Cyber?
Nano Banana Pro (Gemini 3 Pro Image Preview) is available on Google AI Studio, GCP Vertex AI, and OpenRouter. GPT-5.4-Cyber is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Nano Banana Pro (Gemini 3 Pro Image Preview) over GPT-5.4-Cyber?
GPT-5.4-Cyber is safer overall; choose Nano Banana Pro (Gemini 3 Pro Image Preview) when provider fit matters. If your workload also depends on provider fit, start with Nano Banana Pro (Gemini 3 Pro Image Preview); if it depends on reasoning depth, run the same evaluation with GPT-5.4-Cyber.
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Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.