@OpenRouter· @openrouter · X·· 2026-05-29精选AI 评分69
AI 导读
阶跃星辰发布 Step 3.7 Flash，主打 agent 效率，采用 198B 稀疏 MoE、约 11B 激活、256K 上下文和 3 级推理，以 Apache 2.0 开放权重。该模型在 ClawEval-1.1 得 67.1、SimpleVQA Search 得 79.2 均列第一，SWE-PRO 得 56.3，并支持 Claude Code、MCP 等工具调用，可在 Mac Studio M4 Max、DGX Spark 等设备本地运行。
推荐理由
从开放权重和速度成本平衡切入 agent 场景，读者可对照其编程与搜索评测及本地部署支持。
正文
Read more in @StepFun_ai’s launch post:
⚡️ Step 3.7 Flash is here: The new frontier is agent efficiency. #1 ClawEval-1.1 (67.1), #1 SimpleVQA Search (79.2), #2 SWE-PRO (56.3), 95.3 on V* Python. Open weights under Apache 2.0. Built for agentic, coding, search, and multimodal workflows — balancing speed, cost, and reliable execution. - 400 TPS. 198B sparse MoE, ~11B active. 256K context, 3 reasoning levels. - Understands UIs, charts, docs, images — then writes code or calls tools to act on what it sees. - Web + visual search reaches further: more sources, deeper follow-up. - Reliable tool use — less drift, fewer broken toolcalls. 98%+ on τ²-bench across all difficulty levels. - Works with Claude Code, KiloCode, Hermes Agent, OpenClaw, and protocols like MCP. - Runs locally on Mac Studio M4 Max, DGX Spark, AMD AI Max+ 395. GitHub: github.com/stepfun-ai/Step-3… HuggingFace: huggingface.co/stepfun-ai/St… GGUF: huggingface.co/stepfun-ai/St… ModelScope: modelscope.cn/models/stepfun… API: platform.stepfun.ai Blog: static.stepfun.com/blog/step…在 X 查看被引用的帖子
来源：@OpenRouter · x.com