Gemini 3.1 Pro vs GPT-5.4 nano
Gemini 3.1 Pro vs GPT-5.4 nano: GPT-5.4 nano is cheaper for input-heavy usage ($0.20/M vs $2.00/M input tokens), while Gemini 3.1 Pro is better for long-context tasks (1,000,000 tokens).
Direct answer: choose GPT-5.4 nano for lower token spend and choose Gemini 3.1 Pro when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Gemini 3.1 Pro
GPT-5.4 nano
Cost Differences
GPT-5.4 nano costs less than Gemini 3.1 Pro
Quick Recommendation
Winner for direct API pricing: GPT-5.4 nano. At the default workload, GPT-5.4 nano saves about $21.525/month ($261.8875/year) versus Gemini 3.1 Pro.
Feature Comparison
| Feature | Gemini 3.1 Pro | GPT-5.4 nano |
|---|---|---|
| Provider | OpenAI | |
| Input Price | $2.00/1M tokens | $0.20/1M tokens |
| Output Price | $12.00/1M tokens | $1.25/1M tokens |
| Context Window | 1,000,000 tokens | 128,000 tokens |
| Max Output | 65,536 tokens | 8,192 tokens |
| Category | flagship | efficient |
| Capabilities | textvisionaudiovideocodereasoning | text |
| Release Date | 2/19/2026 | 3/6/2026 |
Gemini 3.1 Pro vs GPT-5.4 nano: Which Should You Choose?
Choosing between Gemini 3.1 Pro and GPT-5.4 nano depends on your priorities: cost efficiency, context length, or raw capability. GPT-5.4 nano is the more affordable option at $0.20/1M input tokens — 90% cheaper than Gemini 3.1 Pro. Meanwhile, Gemini 3.1 Pro offers a significantly larger context window at 1,000,000 tokens vs 128,000 for GPT-5.4 nano.
These models come from different providers — Google and OpenAI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Google, switching to OpenAIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Gemini 3.1 Pro is a flagship model while GPT-5.4 nano is efficient. This means they're optimized for different workloads. Gemini 3.1 Pro is built for complex tasks that require deeper reasoning, while GPT-5.4 nano offers better value for routine operations.
Output costs matter too. Gemini 3.1 Pro charges $12.00/1M output tokens vs $1.25 for GPT-5.4 nano. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. GPT-5.4 nano has the edge here at $1.25/1M output tokens.
Multimodal capabilities: Gemini 3.1 Pro supports vision (image inputs) while GPT-5.4 nano is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Gemini 3.1 Pro when:
- • You need a larger context window (1,000,000 tokens)
- • You need more capabilities (vision, audio, video, code, reasoning)
- • You need longer outputs (up to 65,536 tokens)
- • You're already using Google's API ecosystem
Choose GPT-5.4 nano when:
- • Budget is a primary concern
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Pros and Caveats at a Glance
Gemini 3.1 Pro
- • Input pricing: $2.00/M tokens
- • Output pricing: $12.00/M tokens
- • Context window: 1,000,000 tokens
- • Max output: 65,536 tokens
Watch out for
- • Higher input cost than GPT-5.4 nano
- • Higher output cost than GPT-5.4 nano
GPT-5.4 nano
- • Input pricing: $0.20/M tokens
- • Output pricing: $1.25/M tokens
- • Context window: 128,000 tokens
- • Max output: 8,192 tokens
Watch out for
- • Smaller context window than Gemini 3.1 Pro
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Gemini 3.1 Pro (Google)
GPT-5.4 nano (OpenAI)
Start using Gemini 3.1 Pro today
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Sign Up for OpenAI →Frequently Asked Questions
Which is cheaper, Gemini 3.1 Pro or GPT-5.4 nano?▼
What is the context window difference between Gemini 3.1 Pro and GPT-5.4 nano?▼
Which model is better for AI Chatbot?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare Google and OpenAI API pricing beyond this model matchup?▼
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