Gemini 3.1 Pro vs GPT-5.5
Side-by-side comparison of pricing, context window, modalities, licensing, and strengths — with practical guidance on which model fits which workload.
| Spec | Gemini 3.1 Pro | GPT-5.5 |
|---|---|---|
| Provider | OpenAI | |
| Context window | 1M tokens | 1M tokens |
| Input price (per 1M tokens) | $2.00 | $5.00 |
| Output price (per 1M tokens) | $12.00 | $30.00 |
| Example workload (10M in + 2M out) | $44.00 / month | $110.00 / month |
| Modalities | text, image, audio, video, code | text, image, audio, code |
| Knowledge cutoff | Not disclosed | Not disclosed |
| Release date | 2026 | 2026 |
| License | Proprietary | Proprietary |
| Strengths | Multimodal reasoning, Computer use, Video input, Long context | Flagship reasoning, Agentic tool use, Multimodal, Coding |
| Open weights | No | No |
Verdict
Google’s multimodal flagship against OpenAI’s. Gemini 3.1 Pro is the price aggressor at $2/$12 per million tokens (rising to $4/$18 past 200K input) versus GPT-5.5’s $5/$30, and it uniquely accepts video input and leads on computer-use benchmarks. GPT-5.5 answers with audio modality, a slightly larger effective context, and the deepest third-party integration ecosystem in the industry. On raw reasoning the two trade wins by task — run both on your own evals before committing.
When to choose Gemini 3.1 Pro
Pick Gemini 3.1 Pro for video understanding, computer-use agents, lower per-token cost, and Google Cloud integration.
When to choose GPT-5.5
Pick GPT-5.5 for audio interactions, ecosystem breadth, and the most battle-tested function-calling stack.
Prices and specs reflect published provider information and change frequently — always confirm on the provider's pricing page before committing to a workload.
About
This page compares Gemini 3.1 Pro (Google) and GPT-5.5 (OpenAI) side by side across the specs that actually drive a model decision: API pricing per million tokens, context window size, supported modalities, licensing and open-weights status, knowledge cutoff, and headline strengths. A worked example projects the monthly cost of a typical workload (10M input + 2M output tokens) on each model, and an editorial verdict summarises when to choose which. Spec data comes from the same registry that powers our full model comparison table, so figures stay consistent across the site.
How to use
- 1 Scan the spec table for the head-to-head numbers — pricing, context window, modalities, license, and strengths for Gemini 3.1 Pro and GPT-5.5.
- 2 Check the example-workload row to see what a realistic monthly volume costs on each model.
- 3 Read the verdict and the two "when to choose" cards to map each model to your use case.
- 4 Use the FAQ for quick answers on price, context window, and self-hosting.
- 5 Estimate your own numbers with the AI cost calculator and token counter linked at the bottom, or jump to a related comparison.
- Which is cheaper: Gemini 3.1 Pro or GPT-5.5?
- Gemini 3.1 Pro is cheaper per token: $2.00 input / $12.00 output per 1M tokens, versus $5.00 / $30.00 for GPT-5.5. Actual costs depend on your input-to-output ratio — try the AI cost calculator for your own numbers.
- Which has the larger context window?
- Both models offer roughly the same 1M-token context window, so raw capacity won't be the deciding factor — check instead whether either provider charges premium rates for long prompts.
- Can I self-host either model?
- No — both models are proprietary and available only through their providers' APIs or cloud platforms.
- How should I test which model is better for my use case?
- Benchmarks are a starting point, not an answer. Run both models on 20–50 examples of your real task and compare outputs blind. Use our token counter to estimate prompt sizes and the cost calculator to project monthly spend before committing.
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