DeepSeek V3.2 Exp vs Kimi K2 0711
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 V3.2 Exp and Kimi K2 0711.
DeepSeek V3.2 Exp
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
Kimi K2 0711
Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...
Technical Specifications
| Specification | DeepSeek V3.2 Exp | Kimi K2 0711 |
|---|---|---|
| Provider | DeepSeek | Moonshot AI |
| Context Window | 163,840 tokens | 131,072 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | self hostable | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-09-29 | 2025-07-11 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V3.2 Exp
$0.27
Kimi K2 0711
$0.57
Output Price per Million Tokens
DeepSeek V3.2 Exp
$0.41
Kimi K2 0711
$2.30
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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 V3.2 Exp Quirks & Gotchas
No developer gotchas reported.
Kimi K2 0711 Quirks & Gotchas
No developer gotchas reported.