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README.md

+# Step-3.5-Flash
+## 论文
+[Step-3.5-Flash](https://arxiv.org/pdf/2602.10604)
+
+## 模型简介
+
+Step 3.5 Flash专为极致效率而生，具备前沿的推理能力和卓越的智能体（Agent）性能。该模型基于稀疏混合专家（MoE）架构，拥有 1960 亿参数，但处理每个 Token 时仅需选择性激活 110 亿参数。这种极高的“智能密度”使其推理深度足以媲美顶级闭源模型，同时兼顾了实时交互所需的敏捷响应速度。
+
+**其核心能力包括**：
+
+1.兼具前沿智能与极速响应： 聊天机器人重在“读”，而智能体必须快在“想”。得益于三路多Token预测（ MTP-3）技术，Step 3.5 Flash 在典型场景下的生成吞吐量可达 100–300 tok/s（单流代码任务峰值可达 350 tok/s）。复杂多步骤的推理链也能实现即时响应。
+
+2.代码与智能体的稳健引擎： Step 3.5 Flash 专为智能体任务打造，集成了可扩展的强化学习（RL）框架，驱动模型持续自我进化。它在 SWE-bench Verified 分数达到74.4%，在 Terminal-Bench 2.0 测试中分数达 51.0%，证明了其在处理复杂、长程任务时坚如磐石的稳定性。
+
+3.高效的长上下文处理： Step 3.5 Flash采用 3:1 的滑动窗口注意力（SWA）比例 （即每层全注意力层搭配三层 SWA 层），该模型支持极具成本效益的 256K 上下文窗口。这种混合机制确保了在处理海量数据或超长代码库时性能不减，同时显著降低了传统长上下文模型常见的计算开销。
+
+4.便捷的本地部署： Step 3.5 Flash 专为易用性优化，将高性能推理带入本地环境。用户在高端消费级硬件（如 Mac Studio M4 Max, NVIDIA DGX Spark）上即可部署，在确保数据隐私的同时，性能毫不妥协。
+
+Step 3.5 Flash 在推理、编程和智能体能力三个维度的性能表现。左侧开源模型按总参数量排序，右侧则列出了顶尖的闭源模型。为确保一致性，xbench-DeepSearch 的分数均取自官方发布数据。图中的阴影部分展示了 Step 3.5 Flash 启用“并行思考 (Parallel Thinking)”后的性能提升。
+
+<div align=center>
+    <img src="./doc/step-bar-chart.png"/>
+</div>
+
+## 环境依赖
+| 软件 |                    版本                     |
+| :------: |:-----------------------------------------:|
+| DTK |                   26.04                   |
+| python |                  3.10.12                  |
+| transformers |                4.57.6                 |
+| vllm |       0.15.1+das.opt1.alpha.dtk2604.20260220.g2799735a       |
+| triton | 3.3.0+das.opt2.dtk2604.torch291.20260210.g1329924c |
+| torch | 2.9.0+das.opt1.dtk2604.20260206.g275d08c2 |
+
+当前仅支持以下镜像: harbor.sourcefind.cn:5443/dcu/admin/base/custom:vllm0.15.1-ubuntu22.04-dtk26.04-0130-py3.10-20260220
+
+**注意**：该镜像版本暂不稳定，建议试用，生产环境不推荐部署
+
+
+- 挂载地址`-v` 根据实际模型情况修改
+```bash
+docker run -it \
+    --shm-size 200g \
+    --network=host \
+    --name Step-3.5-Flash \
+    --privileged \
+    --device=/dev/kfd \
+    --device=/dev/dri \
+    --device=/dev/mkfd \
+    --group-add video \
+    --cap-add=SYS_PTRACE \
+    --security-opt seccomp=unconfined \
+    -u root \
+    -v /opt/hyhal/:/opt/hyhal/:ro \
+    -v /path/your_code_data/:/path/your_code_data/ \
+    harbor.sourcefind.cn:5443/dcu/admin/base/custom:vllm0.15.1-ubuntu22.04-dtk26.04-0130-py3.10-20260220 bash
+```
+更多镜像可前往[光源](https://sourcefind.cn/#/service-list)下载使用。
+
+关于本项目DCU显卡所需的特殊深度学习库可从[光合](https://developer.sourcefind.cn/tool/)开发者社区下载安装，pycountry库需要单独安装：
+```
+pip install pycountry
+```
+
+## 数据集
+暂无
+
+## 训练
+暂无
+
+## 推理
+### vllm
+#### 单机推理
+
+启动vllm server
+
+```bash
+## serve启动
+vllm serve stepfun-ai/Step-3.5-Flash \
+    --port 8001 \
+    --tensor-parallel-size 16 \
+    --distributed-executor-backend ray \
+    --enable-expert-parallel \
+    --disable-cascade-attn \
+    --reasoning-parser step3p5 \
+    --enable-auto-tool-choice \
+    --tool-call-parser step3p5 \
+    --hf-overrides '{"num_nextn_predict_layers": 1}' \
+    --speculative_config '{"method": "step3p5_mtp", "num_speculative_tokens": 1}' \
+    --trust-remote-code 
+
+## client访问
+curl http://localhost:8001/v1/chat/completions   \
+    -H "Content-Type: application/json"  \
+    -d '{
+        "model": "stepfun-ai/Step-3.5-Flash",
+        "messages": [
+            {
+                "role": "user",
+                "content": "牛顿提出了哪三大运动定律？请简要说明。"
+            }
+        ]
+    }'
+```
+
+## 效果展示
+<div align=center>
+    <img src="./doc/result-dcu.png"/>
+</div>
+
+### 精度
+DCU与GPU精度一致，推理框架：vllm。
+
+## 预训练权重
+|  模型名称  | 权重大小 | DCU型号  | 最低卡数需求 |         下载地址          |
+|:------:|:----:|:----------:|:------:|:---------------------:|
+| Step-3.5-Flash | 199B | BW1000 |   8    | [Hugging Face](https://huggingface.co/stepfun-ai/Step-3.5-Flash) |
+
+## 源码仓库及问题反馈
+- https://developer.sourcefind.cn/codes/modelzoo/step-3.5-flash_vllm
+
+## 参考资料
+- https://github.com/stepfun-ai/Step-3.5-Flash

model.properties

+# 模型唯一标识
+modelCode=2137
+# 模型名称
+modelName=step-3.5-flash_vllm
+# 模型描述
+modelDescription=Step 3.5 Flash专为极致效率而生，具备前沿的推理能力和卓越的智能体（Agent）性能。
+# 运行过程
+processType=推理
+# 算法类别
+appCategory=对话问答
+# 框架类型
+frameType=vllm
+# 加速卡类型
+accelerateType=BW1000
\ No newline at end of file