Just when there was growing concern that DeepSeek was a flash in the pan, the Chinese AI lab released the production ready DeepSeek-V3.2, one of two best open source and a top-five overall large language model.
DeepSeek-V3.2 performs impressively well on a wide range of benchmarks, per its own reporting as well as the independent tests. As of the time of this writing, DeepSeek-V3.2 stands in fifth place on the Artificial Analysis index, behind Kimi K2 Thinking and ahead of Grok 4.
DeepSeek V3.2 is the #2 most intelligent open weights model and also ranks ahead of Grok 4 and Claude Sonnet 4.5 (Thinking) – it takes DeepSeek Sparse Attention out of ‘experimental’ status and couples it with a material boost to intelligence@deepseek_ai V3.2 scores 66 on the… pic.twitter.com/1jidyVzR8g— Artificial Analysis (@ArtificialAnlys) December 3, 2025
But as impressive as the performance of the model is its cost-effectiveness. DeepSeek-V3.2 costs $0.28 per million input tokens and $0.48 per million output tokens. It is also more efficient on token usage than it predecessors ($54 for running the Artificial Analysis tests in comparison to $380 for DeepSeek-R1 0528) as well as other competing models ($380 for Kimi K2 Thinking, $859 for GPT-5.1 High, and $1,201 for Gemini 3 Pro). It stands out on the Pareto curve of cost/intelligence among both open and closed models.
