翼月菌 - e/acc

@HiTw93 内置免费的 GLM-5、MiniMax-M2.5 以及 Kimi-K2.5，我是经常用它来做一些简单任务，复杂编程还是得上 cc/codex😄

@LeaderOnePro 我看看有没有其他小伙伴用 iflow，这个是哪儿更好哦

Kaku will soon show usage for Claude Code, Codex, Kimi, Gemini, GitHub, and Copilot directly in the terminal, with no setup needed. You’ll also be able to switch accounts and change models in one place, which feels much simpler than opening another app and uses far fewer resources. Any other coding CLIs you think I should add next?

GPT-5.4 is launching, available now in the API and Codex and rolling out over the course of the day in ChatGPT. It's much better at knowledge work and web search, and it has native computer use capabilities. You can steer it mid-response, and it supports 1m tokens of context.

🚀 Introducing the Qwen 3.5 Medium Model Series Qwen3.5-Flash · Qwen3.5-35B-A3B · Qwen3.5-122B-A10B · Qwen3.5-27B ✨ More intelligence, less compute. • Qwen3.5-35B-A3B now surpasses Qwen3-235B-A22B-2507 and Qwen3-VL-235B-A22B — a reminder that better architecture, data quality, and RL can move intelligence forward, not just bigger parameter counts. • Qwen3.5-122B-A10B and 27B continue narrowing the gap between medium-sized and frontier models — especially in more complex agent scenarios. • Qwen3.5-Flash is the hosted production version aligned with 35B-A3B, featuring: – 1M context length by default – Official built-in tools 🔗 Hugging Face: huggingface.co/collections/Qw… 🔗 ModelScope: modelscope.cn/collections/Qw… 🔗 Qwen3.5-Flash API: modelstudio.console.alibabacloud.com/ap-southeast-1… Try in Qwen Chat 👇 Flash: chat.qwen.ai/?models=qwen3.… 27B: chat.qwen.ai/?models=qwen3.… 35B-A3B: chat.qwen.ai/?models=qwen3.… 122B-A10B: chat.qwen.ai/?models=qwen3.… Would love to hear what you build with it.

Gemini 3.1 Pro is here. We’ve significantly improved the model’s overall intelligence so it can solve tougher problems. 🧵

🚀 Qwen3.5-397B-A17B is here: The first open-weight model in the Qwen3.5 series. 🖼️Native multimodal. Trained for real-world agents. ✨Powered by hybrid linear attention + sparse MoE and large-scale RL environment scaling. ⚡8.6x–19.0x decoding throughput vs Qwen3-Max 🌍201 languages & dialects 📜Apache2.0 licensed 🔗Dive in: GitHub: github.com/QwenLM/Qwen3.5 Chat: chat.qwen.ai API：modelstudio.console.alibabacloud.com/ap-southeast-1… Qwen Code: github.com/QwenLM/qwen-co… Hugging Face: huggingface.co/collections/Qw… ModelScope: modelscope.cn/collections/Qw… blog: qwen.ai/blog?id=qwen3.5

GPT-5.3-Codex-Spark is now in research preview. You can just build things—faster.

Today, we updated Gemini 3 Deep Think to further accelerate modern science, research and engineering. With 84.6% on ARC-AGI-2 and a new standard on Humanity’s Last Exam, see how this specialized reasoning mode is advancing research & development 🧵↓

Introducing M2.5, an open-source frontier model designed for real-world productivity. - SOTA performance at coding (SWE-Bench Verified 80.2%), search (BrowseComp 76.3%), agentic tool-calling (BFCL 76.8%) & office work. - Optimized for efficient execution, 37% faster at complex tasks. - At $1 per hour with 100 tps, infinite scaling of long-horizon agents now economically possible MiniMax Agent: agent.minimax.io API: platform.minimax.io CodingPlan: platform.minimax.io/subscribe/codi…

Introducing GLM-5: From Vibe Coding to Agentic Engineering GLM-5 is built for complex systems engineering and long-horizon agentic tasks. Compared to GLM-4.5, it scales from 355B params (32B active) to 744B (40B active), with pre-training data growing from 23T to 28.5T tokens. Try it now: chat.z.ai Weights: huggingface.co/zai-org/GLM-5 Tech Blog: z.ai/blog/glm-5 OpenRouter (Previously Pony Alpha): openrouter.ai/z-ai/glm-5 Rolling out from Coding Plan Max users: z.ai/subscribe

@yangyi The Great Gatsby

"Whenever you feel like criticizing any one," he told me, "just remember that all the people in this world haven't had the advantages that you've had."

@ShenHuang_ @XianyuLi @Kimi_Moonshot github.com/MoonshotAI/kim…

@XianyuLi @Kimi_Moonshot Kimi K2.5 有类似claude code那种终端用么？

这么强？@Kimi_Moonshot

Introducing Claude Opus 4.6. Our smartest model got an upgrade. Opus 4.6 plans more carefully, sustains agentic tasks for longer, operates reliably in massive codebases, and catches its own mistakes. It’s also our first Opus-class model with 1M token context in beta.

GPT-5.3-Codex is here! *Best coding performance (57% SWE-Bench Pro, 76% TerminalBench 2.0, 64% OSWorld). *Mid-task steerability and live updates during tasks. *Faster! Less than half the tokens of 5.2-Codex for same tasks, and >25% faster per token! *Good computer use.

@Cldeop 测试 xAI

小彩蛋：现在给这条帖子点赞会有SpaceX小火箭哦！一起来试试吧！

🥝 Meet Kimi K2.5, Open-Source Visual Agentic Intelligence. 🔹 Global SOTA on Agentic Benchmarks: HLE full set (50.2%), BrowseComp (74.9%) 🔹 Open-source SOTA on Vision and Coding: MMMU Pro (78.5%), VideoMMMU (86.6%), SWE-bench Verified (76.8%) 🔹 Code with Taste: turn chats, images & videos into aesthetic websites with expressive motion. 🔹 Agent Swarm (Beta): self-directed agents working in parallel, at scale. Up to 100 sub-agents, 1,500 tool calls, 4.5× faster compared with single-agent setup. - 🥝 K2.5 is now live on kimi.com in chat mode and agent mode. 🥝 K2.5 Agent Swarm in beta for high-tier users. 🥝 For production-grade coding, you can pair K2.5 with Kimi Code: kimi.com/code - 🔗 API: platform.moonshot.ai 🔗 Tech blog: kimi.com/blogs/kimi-k2-… 🔗 Weights & code: huggingface.co/moonshotai/Kim…

🚀 Introducing LongCat-Flash-Thinking-2601 — A version built for deep and general agentic thinking. ✨ Highlights: 🤖 Top Tier Agent Capabilities 🔹 Performance: Top tier benchmark results (TIR / Agentic Search / Agentic Tool Use) ; superb generalization ability, outperforming Claude in complex, random tasks 🔹 Env Scaling: Multiple automaticly constructed high-quality environments; dense dependency graph 🔹 Multi-Env RL: Extended DORA (our RL infra), supporting large-scale multi-environment agentic training 🛡️ Real-World Robustness 🔹 Performance: Solid performance in messy, uncertain scenarios (Vita-Noise & Tau^2-Noise) 🔹 Noise Analysis: Systematically analyzed real-world noise in agentic scenarios 🔹 Curriculum RL: Increasing noise type & intensity while training 🎯 Heavy Thinking Mode ​🔹 Parallel Thinking: Expands breadth via multiple independent reasoning tracks 🔹 Iterative Summarization: Enhances depth by using a summary model to synthesize outputs, supporting iterative reasoning loops 📅 One more thing: 1M-token context via Zigzag Attention is coming soon. 🔍 Try it now: longcat.ai ✅ API access for this version is also available. Hugging Face: huggingface.co/meituan-longca… GitHub: github.com/meituan-longca…

@yetone Agent 家居（

智能家居（

GLM-4.7 is here! GLM-4.7 surpasses GLM-4.6 with substantial improvements in coding, complex reasoning, and tool usage, setting new open-source SOTA standards. It also boosts performance in chat, creative writing, and role-play scenarios. Default Model for Coding Plan: z.ai/subscribe Try it now: chat.z.ai Weights: huggingface.co/zai-org/GLM-4.7 Tech Blog: z.ai/blog/glm-4.7

Introducing Claude Opus 4.5: the best model in the world for coding, agents, and computer use. Opus 4.5 is a step forward in what AI systems can do, and a preview of larger changes to how work gets done.