DeepSeek-V3.1-Base

DeepSeek-V3.1 Introduction DeepSeek-V3.1 is a hybrid model that supports both thinking mode and non-thinking mode. Compared to the previous version, this upgrade brings improvements in multiple aspects: **Hybrid thinking mode**: One model supports both thinking mode and non-thinking mode by changing the chat template. **Smarter tool calling**: Through post-training optimization, the model's performance in tool usage and agent tasks has significantly improved. **Higher thinking efficiency**: DeepSeek-V3.1-Think achieves comparable answer quality to DeepSeek-R1-0528, while responding more quickly. DeepSeek-V3.1 is post-trained on the top of DeepSeek-V3.1-Base, which is built upon the original V3 base checkpoint through a two-phase long context extension approach, following the methodology outlined in the original DeepSeek-V3 report. We have expanded our dataset by collecting additional long documents and substantially extending both training phases. The 32K extension phase has been increased 10-fold to 630B tokens, while the 128K extension phase has been extended by 3.3x to 209B tokens. Additionally, DeepSeek-V3.1 is trained using the **UE8M0 FP8 scale data format on both model weights and activations** to ensure compatibility with microscaling data formats. Please refer to DeepGEMM for more details. Model Downloads | **Model** | **#Total Params** | **#Activated Params** | **Context Length** | **Download** | | :------------: | :------------: | :------------: | :------------: | :------------: | | DeepSeek-V3.1-Base | 671B | 37B | 128K | HuggingFace \| ModelScope | | DeepSeek-V3.1 | 671B | 37B | 128K | HuggingFace \| ModelScope | Chat Template The details of our chat template is described in `tokenizer_config.json` and `assets/chat_template.jinja`. Here is a brief description. Non-Thinking First-Turn Prefix: ` {system prompt} {query} ` With the given prefix, DeepSeek V3.1 generates responses to queries in non-thinking mode. Unlike DeepSeek V3, it introduces an additiona