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While typical models spend 1–2% of their budget on post-training, v3.2 allocated . Space v3.2

DeepSeek-V3.2 proves that you don't need a trillion-dollar data center to achieve state-of-the-art performance. By optimizing architecture rather than just "scaling up," this release democratizes high-level AI reasoning for the open-source community. Other "v3.2" Highlights in the Space Below is a blog post template centered on

You get faster inference and lower hardware requirements without sacrificing the model's "brainpower." 2. Intentional Post-Training Scaling Space v3.2