.. _models_llm_deepseek-v3.2-exp: ======================================== DeepSeek-V3.2-Exp ======================================== - **Context Length:** 163840 - **Model Name:** DeepSeek-V3.2-Exp - **Languages:** en, zh - **Abilities:** chat, reasoning, hybrid, tools - **Description:** We are excited to announce the official release of DeepSeek-V3.2-Exp, an experimental version of our model. As an intermediate step toward our next-generation architecture, V3.2-Exp builds upon V3.1-Terminus by introducing DeepSeek Sparse Attention—a sparse attention mechanism designed to explore and validate optimizations for training and inference efficiency in long-context scenarios. Specifications ^^^^^^^^^^^^^^ Model Spec 1 (pytorch, 671 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 671 - **Quantizations:** none - **Engines**: vLLM, Transformers - **Model ID:** deepseek-ai/DeepSeek-V3.2-Exp - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name DeepSeek-V3.2-Exp --size-in-billions 671 --model-format pytorch --quantization ${quantization} Model Spec 2 (awq, 671 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** awq - **Model Size (in billions):** 671 - **Quantizations:** AWQ, AWQ-Lite - **Engines**: Transformers - **Model ID:** QuantTrio/DeepSeek-V3.2-Exp-{quantization} - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name DeepSeek-V3.2-Exp --size-in-billions 671 --model-format awq --quantization ${quantization}