Gemini 2.0 Flash vs GPT-4.1 nano
Pricing verdict: Gemini 2.0 Flash vs GPT-4.1 nano: pricing is a tie at $0.10/M input and $0.40/M output. The real choice is context: Gemini 2.0 Flash is better for long-context tasks (1,000,000 tokens vs 128,000).
Direct answer: pricing is a tie. Choose Gemini 2.0 Flash for the larger 1M context window, or pick GPT-4.1 nano if 128K is already enough for your workload.
Compare API pricing, input and output token costs, context windows, and monthly estimates on one page so you can pick the right model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Gemini 2.0 Flash
GPT-4.1 nano
Cost Differences
Both models cost the same at the default workload.
Quick Recommendation
Direct API pricing is a tie at the default workload: both land around $0.90/month. Pick Gemini 2.0 Flash if you need the larger 1M context window; otherwise choose the model that better fits your workflow.
Feature Comparison
| Feature | Gemini 2.0 Flash | GPT-4.1 nano |
|---|---|---|
| Provider | OpenAI | |
| Input Price | $0.10/1M tokens | $0.10/1M tokens |
| Output Price | $0.40/1M tokens | $0.40/1M tokens |
| Context Window | 1,000,000 tokens | 128,000 tokens |
| Max Output | 32,768 tokens | 8,192 tokens |
| Category | efficient | efficient |
| Capabilities | textvisionaudiocode | text |
| Release Date | 12/11/2024 | 4/14/2025 |
Gemini 2.0 Flash vs GPT-4.1 nano: Which Should You Choose?
Choosing between Gemini 2.0 Flash and GPT-4.1 nano depends on your priorities: cost efficiency, context length, or raw capability. Both models cost the same on input and output tokens, so raw price is a tie. Meanwhile, Gemini 2.0 Flash offers a significantly larger context window at 1,000,000 tokens vs 128,000 for GPT-4.1 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.
Both models are in the efficient category, making this a direct head-to-head comparison. At scale — say 10,000 requests per day — direct API pricing stays tied, so the real decision is context, latency, and provider fit.
Output costs matter too. Gemini 2.0 Flash charges $0.40/1M output tokens vs $0.40 for GPT-4.1 nano.
Multimodal capabilities: Gemini 2.0 Flash supports vision (image inputs) while GPT-4.1 nano is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Gemini 2.0 Flash when:
- • You need a larger context window (1,000,000 tokens)
- • You need more capabilities (vision, audio, code)
- • You need longer outputs (up to 32,768 tokens)
- • You're already using Google's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose GPT-4.1 nano when:
- • You're already using OpenAI's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Pros and Caveats at a Glance
Gemini 2.0 Flash
- • Input pricing: $0.10/M tokens
- • Output pricing: $0.40/M tokens
- • Context window: 1,000,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Trade-offs are minor in this matchup.
GPT-4.1 nano
- • Input pricing: $0.10/M tokens
- • Output pricing: $0.40/M tokens
- • Context window: 128,000 tokens
- • Max output: 8,192 tokens
Watch out for
- • Smaller context window than Gemini 2.0 Flash
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Gemini 2.0 Flash (Google)
GPT-4.1 nano (OpenAI)
Start using Gemini 2.0 Flash today
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Sign Up for OpenAI →Frequently Asked Questions
Which is cheaper, Gemini 2.0 Flash or GPT-4.1 nano?▼
What is the context window difference between Gemini 2.0 Flash and GPT-4.1 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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