DeepSeek R1 vs o1
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 o1.
DeepSeek R1
A premier reasoning model employing large-scale reinforcement learning. Displays specialized math, coding, and logical validation capabilities comparable to OpenAI's o1.
o1
The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...
Technical Specifications
| Specification | DeepSeek R1 | o1 |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Context Window | 163,840 tokens | 200,000 tokens |
| Agent Suitability | 78/100 | 88/100 |
| Time to First Token (TTFT) | 1800 ms | 2500 ms |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-01-20 | 2024-12-17 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek R1
$0.70
o1
$15.00
Output Price per Million Tokens
DeepSeek R1
$2.50
o1
$60.00
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
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
o1 Quirks & Gotchas
- ▸Reasoning model — high latency by design, not for real-time use
- ▸Best for complex math/code reasoning where accuracy > speed
- ▸Use o3-mini when you need reasoning with lower latency