deepseek-v3.2 by openrouter - AI Model Details, Pricing, and Performance Metrics

deepseek
deepseek-v3.2
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deepseek

deepseek-v3.2

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DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism that reduces training and inference cost while preserving quality in long-context scenarios. A scalable reinforcement learning post-training framework further improves reasoning, with reported performance in the GPT-5 class, and the model has demonstrated gold-medal results on the 2025 IMO and IOI. V3.2 also uses a large-scale agentic task synthesis pipeline to better integrate reasoning into tool-use settings, boosting compliance and generalization in interactive environments. Users can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config)

Released
Dec 1, 2025
Knowledge
Jun 4, 2025
Context
163840
Input
$0.26 / 1M tokens
Output
$0.39 / 1M tokens
Cached
$0.14 / 1M tokens
Capabilities: tools, reasoning
Accepts: text
Returns: text

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Category Scores

Benchmark Tests

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HLE
22.2
General Knowledge
GPQA
84.0
STEM (Physics, Chemistry, Biology)
SciCode
38.9
Scientific
MMLU-Pro
86.2
General Knowledge
LiveCodeBench
86.2
Programming
AA Math Index
92.0
Mathematics
AA Coding Index
36.7
Programming
AAII
41.6
General

Code Examples

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