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  ---
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  license: mit
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  library_name: transformers
 
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  ---
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  # DeepSeek-V3.1
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@@ -46,7 +47,7 @@ library_name: transformers
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  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:
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- - **Hybrid thinking mode**: One model supports both thinking mode and non-thinking mode by changing the chat template.
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  - **Smarter tool calling**: Through post-training optimization, the model's performance in tool usage and agent tasks has significantly improved.
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@@ -93,7 +94,7 @@ By concatenating the context and the prefix, we obtain the correct prompt for th
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  Prefix:
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  `<|begin▁of▁sentence|>{system prompt}<|User|>{query}<|Assistant|><think>`
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- The prefix of thinking mode is similar to DeepSeek-R1.
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  #### Multi-Turn
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  Prefix:
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  `<|User|>{query}<|Assistant|><think>`
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- The multi-turn template is the same with non-thinking multi-turn chat template. It means the thinking token in the last turn will be dropped but the `</think>` is retained in every turn of context.
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  ### ToolCall
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- Toolcall is supported in non-thinking mode. The format is:
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- `<|begin▁of▁sentence|>{system prompt}{tool_description}<|User|>{query}<|Assistant|></think>` where the tool_description is
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  ```
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  ## Tools
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  We support various code agent frameworks. Please refer to the above toolcall format to create your own code agents. An example is shown in `assets/code_agent_trajectory.html`.
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  ### Search-Agent
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- We design a specific format for searching toolcall in thinking mode, to support search agent.
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  For complex questions that require accessing external or up-to-date information, DeepSeek-V3.1 can leverage a user-provided search tool through a multi-turn tool-calling process.
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@@ -146,7 +147,7 @@ Please refer to the `assets/search_tool_trajectory.html` and `assets/search_pyth
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  | | MMLU-Pro (EM) | 83.7 | 81.2 | 84.8 | 85.0
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  | | GPQA-Diamond (Pass@1) | 74.9 | 68.4 | 80.1 | 81.0
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  | | Humanity's Last Exam (Pass@1) | - | - | 15.9 | 17.7
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- |Search Agent|
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  | | BrowseComp | - | - | 30.0 | 8.9
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  | | BrowseComp_zh | - | - | 49.2 | 35.7
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  | | Humanity's Last Exam (Python + Search) |- | - | 29.8 | 24.8
@@ -164,8 +165,8 @@ Please refer to the `assets/search_tool_trajectory.html` and `assets/search_pyth
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  | | AIME 2025 (Pass@1) | 49.8 | 51.3 | 88.4 | 87.5
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  | | HMMT 2025 (Pass@1) | 33.5 | 29.2 | 84.2 | 79.4 |
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- Note:
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- - Search agents are evaluated with our internal search framework, which uses a commercial search API + webpage filter + 128K context window. Seach agent results of R1-0528 are evaluated with a pre-defined workflow.
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  - SWE-bench is evaluated with our internal code agent framework.
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@@ -204,13 +205,13 @@ This repository and the model weights are licensed under the [MIT License](LICEN
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  ```
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  @misc{deepseekai2024deepseekv3technicalreport,
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- title={DeepSeek-V3 Technical Report},
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  author={DeepSeek-AI},
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  year={2024},
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  eprint={2412.19437},
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  archivePrefix={arXiv},
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  primaryClass={cs.CL},
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- url={https://arxiv.org/abs/2412.19437},
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  }
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  ```
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  ---
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  license: mit
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  library_name: transformers
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+ base_model: deepseek-ai/DeepSeek-V3.1
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  ---
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  # DeepSeek-V3.1
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47
 
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  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:
49
 
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+ - **Hybrid thinking mode**: One model supports both thinking mode and non-thinking mode by changing the chat template.
51
 
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  - **Smarter tool calling**: Through post-training optimization, the model's performance in tool usage and agent tasks has significantly improved.
53
 
 
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  Prefix:
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  `<|begin▁of▁sentence|>{system prompt}<|User|>{query}<|Assistant|><think>`
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+ The prefix of thinking mode is similar to DeepSeek-R1.
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  #### Multi-Turn
 
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  Prefix:
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  `<|User|>{query}<|Assistant|><think>`
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+ The multi-turn template is the same with non-thinking multi-turn chat template. It means the thinking token in the last turn will be dropped but the `</think>` is retained in every turn of context.
108
 
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  ### ToolCall
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+ Toolcall is supported in non-thinking mode. The format is:
111
 
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+ `<|begin▁of▁sentence|>{system prompt}{tool_description}<|User|>{query}<|Assistant|></think>` where the tool_description is
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  ```
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  ## Tools
 
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  We support various code agent frameworks. Please refer to the above toolcall format to create your own code agents. An example is shown in `assets/code_agent_trajectory.html`.
134
 
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  ### Search-Agent
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+ We design a specific format for searching toolcall in thinking mode, to support search agent.
137
 
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  For complex questions that require accessing external or up-to-date information, DeepSeek-V3.1 can leverage a user-provided search tool through a multi-turn tool-calling process.
139
 
 
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  | | MMLU-Pro (EM) | 83.7 | 81.2 | 84.8 | 85.0
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  | | GPQA-Diamond (Pass@1) | 74.9 | 68.4 | 80.1 | 81.0
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  | | Humanity's Last Exam (Pass@1) | - | - | 15.9 | 17.7
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+ |Search Agent|
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  | | BrowseComp | - | - | 30.0 | 8.9
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  | | BrowseComp_zh | - | - | 49.2 | 35.7
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  | | Humanity's Last Exam (Python + Search) |- | - | 29.8 | 24.8
 
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  | | AIME 2025 (Pass@1) | 49.8 | 51.3 | 88.4 | 87.5
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  | | HMMT 2025 (Pass@1) | 33.5 | 29.2 | 84.2 | 79.4 |
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+ Note:
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+ - Search agents are evaluated with our internal search framework, which uses a commercial search API + webpage filter + 128K context window. Seach agent results of R1-0528 are evaluated with a pre-defined workflow.
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  - SWE-bench is evaluated with our internal code agent framework.
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  ```
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  @misc{deepseekai2024deepseekv3technicalreport,
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+ title={DeepSeek-V3 Technical Report},
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  author={DeepSeek-AI},
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  year={2024},
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  eprint={2412.19437},
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  archivePrefix={arXiv},
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  primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2412.19437},
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  }
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  ```
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