DeepSeek R1 vs DeepSeek V4 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 DeepSeek V4 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.
DeepSeek V4 Pro
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...
Technical Specifications
| Specification | DeepSeek R1 | DeepSeek V4 Pro |
|---|---|---|
| Provider | DeepSeek | DeepSeek |
| Context Window | 163,840 tokens | 1,048,576 tokens |
| Agent Suitability | 78/100 | 94/100 |
| Time to First Token (TTFT) | 1800 ms | 280 ms |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-01-20 | 2026-04-24 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek R1
$0.70
DeepSeek V4 Pro
$0.43
Output Price per Million Tokens
DeepSeek R1
$2.50
DeepSeek V4 Pro
$0.87
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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
DeepSeek V4 Pro Quirks & Gotchas
- ▸MoE architecture — cold-start latency on first request, use keep-alive
- ▸Best cost-performance ratio of any frontier model — strong tool calling for agentic use