Model details
DeepSeek-V3.2 is engineered to harmonize high computational efficiency with advanced reasoning and agentic capabilities. At the core of its architecture is the DeepSeek Sparse Attention mechanism, a two-stage process that utilizes a high-speed lightning indexer to scan tokens and a fine-grained selection process to focus only on the most relevant information. This design significantly reduces computational complexity, allowing the model to maintain high performance during long-context scenarios while remaining efficient for daily use.
The model benefits from a robust reinforcement learning framework and a large-scale agentic task synthesis pipeline, which generates training data across thousands of environments to improve instruction-following. This post-training approach enables the model to integrate thinking directly into tool-use workflows. While the standard version serves as a balanced, high-performance daily driver, the high-compute Speciale variant pushes these capabilities further, achieving gold-medal results in competitive mathematics and informatics benchmarks.
Transparent token rates
Rates are shown per one million tokens. Combined means one million input plus one million output tokens.
SiliconFlow
DeepSeek says both models are more efficient and performant than DeepSeek V3.2 due to architectural improvements, and have almost "closed the gap" with current leading models, both open and closed, on reasoning benchmarks.
SiliconFlow
Compare DeepSeek-R1 and DeepSeek-V3.2 across performance, cost, capabilities, and real-world use cases. See which model fits your needs.
SiliconFlow
Compare DeepSeek-V3.1 and DeepSeek-V3.2-Exp across performance, cost, capabilities, and real-world use cases. See which model fits your needs.
SiliconFlow
Compare DeepSeek-V3 and DeepSeek-V3.2 across performance, cost, capabilities, and real-world use cases. See which model fits your needs.
SiliconFlow
DeepSeek released DeepSeek-V3.2, a family of open-source reasoning and agentic AI models. The high compute version, DeepSeek-V3.2-Speciale, performs better than GPT-5 and comparably to Gemini-3.0-Pro
SiliconFlow
A deep technical breakdown of DeepSeek V3.2, examining how training data, synthetic pipelines, sparse attention, and post-training RL shape reasoning and performance.
SiliconFlow
Updated March 2026: Comprehensive guide to DeepSeek V3.2, V4 (expected April 2026), R1/R2 reasoning models, and how to use DeepSeek in Antigravity via the OpenAI compatibility layer.
