DeepSeek R1 vs Gemini 3.5 Flash
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 3.5 Flash.
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 3.5 Flash
Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly optimized for coding proficiency and parallel agentic execution...
Technical Specifications
| Specification | DeepSeek R1 | Gemini 3.5 Flash |
|---|---|---|
| Provider | DeepSeek | |
| Context Window | 163,840 tokens | 1,048,576 tokens |
| Agent Suitability | 78/100 | 88/100 |
| Time to First Token (TTFT) | 1800 ms | 200 ms |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-01-20 | 2026-05-19 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek R1
$0.70
Gemini 3.5 Flash
$1.50
Output Price per Million Tokens
DeepSeek R1
$2.50
Gemini 3.5 Flash
$9.00
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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 3.5 Flash Quirks & Gotchas
- ▸Excellent multimodal performance — native video understanding
- ▸Tool calling via Google's native function_declarations in Vertex AI