Gemini 3.1 Pro Preview Custom Tools vs GPT-5 Nano
A side-by-side comparison of two multimodal models — real specs, pricing, strengths and weaknesses, and a clear verdict on which to choose. Kept current by our agents.
Quick verdict: which should you choose?
Choose Gemini 3.1 Pro Preview Custom Tools if you need
- ✓Choose GPT-5 Nano if you need the lowest output price at $0.4 per million tokens.
- ✓Choose GPT-5 Nano if you need the fastest documented speed of 170.06 tokens per second.
- ✓Choose GPT-5 Nano if you need efficient handling of 400k contexts with text, image, and file inputs.
- ✓Choose GPT-5 Nano if you need lightweight responses for extended document tasks without custom-tool setup.
Choose GPT-5 Nano if you need
- ✓Choose Gemini 3.1 Pro Preview Custom Tools if you need a 1M+ context window.
- ✓Choose Gemini 3.1 Pro Preview Custom Tools if you need flexible extension via custom tools.
- ✓Choose Gemini 3.1 Pro Preview Custom Tools if you need strong cross-modal coherence on mixed inputs.
- ✓Choose Gemini 3.1 Pro Preview Custom Tools if you can accept preview instability and higher $12 per million token pricing.
Verdict
GPT-5 Nano leads on price and measured output speed while supporting text/image/file inputs in a 400k context; Gemini 3.1 Pro Preview Custom Tools leads on raw context size (1M+) and custom-tool extensibility. GPT-5 Nano trades off depth for efficiency and cost; Gemini trades off preview instability and higher cost for larger windows and tool flexibility. Neither has a published intelligence index comparison.
Gemini 3.1 Pro Preview Custom Tools vs GPT-5 Nano: side by side
| Spec | Gemini 3.1 Pro Preview Custom Tools | GPT-5 Nano | Winner |
|---|---|---|---|
| Intelligence | — | 26.8 | Tie |
| Output speed | — | 170 t/s | Tie |
| Output price | $12.00/1M | $0.40/1M | GPT-5 Nano |
| Context | 1049K | 400K | Gemini 3.1 Pro Preview Custom Tools |
| Params | — | — | Tie |
| Type | Proprietary | Proprietary | Tie |
| Provider | OpenAI | Tie |
Detailed analysis
Pricing
Winner: GPT-5 NanoGPT-5 Nano costs $0.4 per million output tokens. Gemini 3.1 Pro Preview Custom Tools costs $12 per million output tokens. The 30x price difference favors GPT-5 Nano for high-volume use.
Context Window
Winner: Gemini 3.1 Pro Preview Custom ToolsGemini 3.1 Pro Preview Custom Tools supports 1,048,756 tokens. GPT-5 Nano supports 400,000 tokens. The larger window enables Gemini to process substantially longer inputs when needed.
Speed
Winner: GPT-5 NanoGPT-5 Nano is documented at 170.06 tokens per second. No speed figure is provided for Gemini 3.1 Pro Preview Custom Tools. GPT-5 Nano's lightweight design is explicitly positioned for faster responses.
Multimodal & Tools
Winner: TieBoth handle multimodal inputs; GPT-5 Nano explicitly lists text, image, and file support while Gemini emphasizes cross-modal coherence. Gemini adds custom-tool extensibility that GPT-5 Nano does not mention.
Gemini 3.1 Pro Preview Custom Tools
Pros
- +Strong cross-modal coherence on mixed inputs
- +Effective use of very large context windows
- +Flexible extension via custom tools
Cons
- –Preview status may include occasional instability
- –Large contexts can increase latency and cost
- –Tool setup requires additional configuration
GPT-5 Nano
Pros
- +Handles very large contexts efficiently
- +Supports text, image, and file inputs
- +Lightweight design for faster responses
- +Practical for extended document tasks
Cons
- –Lower capability depth than full-scale models
- –May struggle with highly complex reasoning
- –Trade-off in advanced task performance
Summary: Gemini 3.1 Pro Preview Custom Tools vs GPT-5 Nano
Select GPT-5 Nano when cost, speed, and practical 400k multimodal document work are priorities. Select Gemini 3.1 Pro Preview Custom Tools when maximum context length and custom-tool capabilities outweigh higher price and preview limitations. The choice hinges on whether efficiency or scale-plus-tools matters more for the workload.
Frequently asked questions
GPT-5 Nano at $0.4 per million output tokens versus Gemini 3.1 Pro Preview Custom Tools at $12 per million output tokens.