#MCP/工具调用

🤝 Day-0 support for MiniCPM5-2B on stable vLLM. ⚡ Dense 2.6B model with 131K native context 🧠 Think / No-Think from the same checkpoint 🔧 Tool Calling support via vLLM’s minicpm5 parser Congrats @OpenBMB on the release, and thanks for keeping it on stock LlamaForCausalLM and opening the training data alongside the weights! 🙌 🔗 http://recipes.vllm.ai/openbmb/MiniCPM5-2B

MiniMax H3 is native in ComfyUI, day zero with the weights. Model highlights: → Text-to-video, prompt only → Image-to-video → First-and-last-frame - control the opening frame, the closing frame, or both → Reference-to-video - carry a subject, a motion, or a voice through the clip → In-place editing - modify a shot you already have instead of regenerating it The capability @MiniMax_AI leads with is multimodal context understanding, and it's what collapses those five tasks into one model. H3 takes images, audio, and video together and resolves them against a prompt that explains how they relate. Download the workflows & learn more in our blog 👇

Introducing Claude Sonnet 5, our most agentic Sonnet yet. It makes plans, uses tools like browsers and terminals, and runs autonomously at a level that just a few months ago required larger and more expensive models.

The open-weight labs did not come to play this week. StepFun dropped Step 3.7 Flash. MiniMax dropped M3. Both with open weights, both already live in Kilo. The "model wars" just got a lot more interesting.

Today @MiniMax_AI ships M3 — the first frontier model purpose-built for computer-use agents. Natively multimodal. One model, almost every real-world task. And today, @sai_borg runs it. Our users are the first to use M3 the way it was designed to be used — on a real desktop, doing real work. This is what model-and-agent alignment looks like. → Try it: http://sai.work

Excited to support Step 3.7 Flash by @StepFun_ai on ZenMux from day one. 🚀 A sparse MoE vision-language model built for agentic, coding, search, multimodal, and long-context workflows. ⚡ 400 TPS, ~11B active params, 256K context, 3 reasoning levels 👁️ understands UIs, charts, docs, and images — then writes code or calls tools to act on what it sees 🔎 built for deeper web + visual search, with more sources and follow-up 🛠️ reliable tool use: less drift, fewer broken tool calls, 98%+ on τ²-bench across difficulty levels 🧠 works with Claude Code, KiloCode, Hermes Agent, OpenClaw, and MCP-style workflows 🖥️ runs locally on Mac Studio M4 Max, DGX Spark, and AMD AI Max+ 395 Try it on ZenMux now → https://zenmux.ai/stepfun/step-3.7-flash One API for capable models. #StepFun #ZenMux #AIAgents #LLM

📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑‍💻 Coding agent, end to end. Frontend prototypes, multi-file refactors, real debugging — nails it. 🗂️ A reliable office and productivity assistant. Get your work done through MCP integrations and multi-agent orchestration. ⏱️ Long-horizon autonomy. 35 hours straight on a kernel optimization task — 1,000+ tool calls, zero hand-holding. 🔌 Scaffold-agnostic. Claude Code, OpenClaw, Qwen Code, or your own stack. Consistent reliability everywhere. API's up on Alibaba Model Studio. You can also take it for a spin on Qwen Studio. Go build something wild!🏃🏃‍♂️ 📖 Blog: https://qwen.ai/blog?id=qwen3.7 ✅ Qwen Studio: https://chat.qwen.ai/?models=qwen3.7-max ⚡️ API：https://modelstudio.console.alibabacloud.com/ap-southeast-1?tab=doc#/doc/?type=model&url=2840914_2&modelId=qwen3.7-max&serviceSite=international