DeepSeek V3.2 Exp vs R1
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 R1.
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...
R1
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....
Technical Specifications
| Specification | DeepSeek V3.2 Exp | R1 |
|---|---|---|
| Provider | DeepSeek | DeepSeek |
| Context Window | 163,840 tokens | 163,840 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-09-29 | 2025-01-20 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V3.2 Exp
$0.27
R1
$0.70
Output Price per Million Tokens
DeepSeek V3.2 Exp
$0.41
R1
$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 V3.2 Exp Quirks & Gotchas
No developer gotchas reported.
R1 Quirks & Gotchas
No developer gotchas reported.