DeepSeek R1 vs Kimi K2 Thinking
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 Kimi K2 Thinking.
DeepSeek R1
A premier reasoning model employing large-scale reinforcement learning. Displays specialized math, coding, and logical validation capabilities comparable to OpenAI's o1.
Kimi K2 Thinking
Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in...
Technical Specifications
| Specification | DeepSeek R1 | Kimi K2 Thinking |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Context Window | 163,840 tokens | 262,144 tokens |
| Agent Suitability | 78/100 | N/A |
| Time to First Token (TTFT) | 1800 ms | N/A |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-01-20 | 2025-11-06 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek R1
$0.70
Kimi K2 Thinking
$0.60
Output Price per Million Tokens
DeepSeek R1
$2.50
Kimi K2 Thinking
$2.50
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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
Kimi K2 Thinking Quirks & Gotchas
No developer gotchas reported.