DeepSeek R1 vs Gemini 3.1 Pro
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for DeepSeek R1 and Gemini 3.1 Pro.
DeepSeek R1
A premier reasoning model employing large-scale reinforcement learning. Displays specialized math, coding, and logical validation capabilities comparable to OpenAI's o1.
Gemini 3.1 Pro
Google's premiere multi-modal model featuring a massive 2 million token context window. Engineered for deep code analysis, video indexing, and long-context reasoning.
Technical Specifications
| Specification | DeepSeek R1 | Gemini 3.1 Pro |
|---|---|---|
| Provider | DeepSeek | |
| Context Window | 163,840 tokens | 2,000,000 tokens |
| Agent Suitability | 78/100 | 93/100 |
| Time to First Token (TTFT) | 1800 ms | 420 ms |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-01-20 | 2026-04-20 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek R1
$0.70
Gemini 3.1 Pro
$2.00
Output Price per Million Tokens
DeepSeek R1
$2.50
Gemini 3.1 Pro
$12.00
Want to test both models live?
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
DeepSeek R1 Quirks & Gotchas
- ▸Reasoning model — not designed for high-frequency tool calling
- ▸Pair with a smaller model (V4 Flash) for routing and use R1 for complex reasoning only
Gemini 3.1 Pro Quirks & Gotchas
- ▸Best model for massive context — 2M token window is class-leading
- ▸Tool calling requires explicit schema definition in Google AI Studio