Gemini 3.1 Pro vs o4-mini Deep Research
Gemini 3.1 Pro vs o4-mini Deep Research: Gemini 3.1 Pro is cheaper for input-heavy usage ($2.00/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 Gemini 3.1 Pro 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
o4-mini Deep Research
Cost Differences
o4-mini Deep Research costs less than Gemini 3.1 Pro
Quick Recommendation
Winner for direct API pricing: o4-mini Deep Research. At the default workload, o4-mini Deep Research saves about $6.00/month ($73.00/year) versus Gemini 3.1 Pro.
Feature Comparison
| Feature | Gemini 3.1 Pro | o4-mini Deep Research |
|---|---|---|
| Provider | OpenAI | |
| Input Price | $2.00/1M tokens | $2.00/1M tokens |
| Output Price | $12.00/1M tokens | $8.00/1M tokens |
| Context Window | 1,000,000 tokens | 200,000 tokens |
| Max Output | 65,536 tokens | 32,768 tokens |
| Category | flagship | reasoning |
| Capabilities | textvisionaudiovideocodereasoning | textreasoningcode |
| Release Date | 2/19/2026 | 6/26/2025 |
Gemini 3.1 Pro vs o4-mini Deep Research: Which Should You Choose?
Choosing between Gemini 3.1 Pro and o4-mini Deep Research depends on your priorities: cost efficiency, context length, or raw capability. o4-mini Deep Research is the more affordable option at $2.00/1M input tokens. Meanwhile, Gemini 3.1 Pro offers a significantly larger context window at 1,000,000 tokens vs 200,000 for o4-mini Deep Research.
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 o4-mini Deep Research is reasoning. This means they're optimized for different workloads. Gemini 3.1 Pro is built for complex tasks that require deeper reasoning, while o4-mini Deep Research offers better value for routine operations.
Output costs matter too. Gemini 3.1 Pro charges $12.00/1M output tokens vs $8.00 for o4-mini Deep Research. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. o4-mini Deep Research has the edge here at $8.00/1M output tokens.
Multimodal capabilities: Gemini 3.1 Pro supports vision (image inputs) while o4-mini Deep Research 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)
- • You need longer outputs (up to 65,536 tokens)
- • You're already using Google's API ecosystem
Choose o4-mini Deep Research when:
- • You're already using OpenAI's API ecosystem
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 output cost than o4-mini Deep Research
o4-mini Deep Research
- • Input pricing: $2.00/M tokens
- • Output pricing: $8.00/M tokens
- • Context window: 200,000 tokens
- • Max output: 32,768 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)
o4-mini Deep Research (OpenAI)
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Sign Up for OpenAI →Frequently Asked Questions
Which is cheaper, Gemini 3.1 Pro or o4-mini Deep Research?▼
What is the context window difference between Gemini 3.1 Pro and o4-mini Deep Research?▼
Which model is better for AI Agent / Agentic Workflows?▼
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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