
Nour Eddine Hamaidi
2.1K posts



built computer use into hermes agent tell it what to do from your phone → it controls your mac no sandbox real desktop, real apps, real time a complex example : diagram on freeform @Teknium @NousResearch @claudeai for more : github.com/NousResearch/h…







速报一波,GLM-5.1 真的猛,应该是从国产模型SOTA要跃升到真正的全球SOTA了,我的 vector-db-bench 直接刷到了第一,我已经在剪视频了,稍后马上为大家带来GLM-5.1详细评测视频~ (另, GPT-5.4-Pro(xhigh) 真的贵, 为了跑这个昨天干进去150刀....其实也算好消息, 当模型价格比我工资贵, 那它就没太多竞争力了...[允悲]) (测试在这里:vector-db-bench.kcores.com)


Just opened PR #3984 to @NousResearch Hermes agent 🔥 3 UX improvements for Telegram DM topics: — /model now works per-thread. Change model in one topic — others stay untouched — Fallback notification: when primary model fails, you see it instantly in chat instead of wondering why the bot switched — Subagent progress now shows the model: 🔀 delegate_task: "..." (model: claude-opus-4-6) All tested live — the agent was literally editing its own code 😄 Also have an older open PR #3165 (voice messages as captions) — still waiting for review @Teknium 👀 P.S. Do you use Telegram DM topics with Hermes? Or just chat without threads?








Here comes AutoClaw. We offer a new solution to run OpenClaw locally on your own machine. - Download and start immediately. No API key required. - Bring any model you like, or use GLM-5-Turbo, optimized for tool calling and multi-step tasks. - Fully local. Your data never leaves your machine. We're giving data control back to Claw users. Meet AutoClaw → autoglm.z.ai/autoclaw/ Join the conversation → discord.gg/jvrbCRSF3x



hey if you're considering nvidia's nemotron cascade 2 for agent coding on your 3090 this might save you time. here's what afew days of testing taught me. speed settled. 187 tok/s flat from 4K to 625K context. 67% faster than qwen 3.5 35B-A3B on the same card. mamba2 is context independent and needs zero flags to get there. for chat, bash scripting, API calls, simple tool use, this model at this speed is unmatched in the 3B active class. but i pushed it harder. gave it the same autonomous coding test i give every model. octopus invaders, a full space shooter game, pixel art enemies, particle systems, audio, HUD, game states. the kind of build that tests whether a model can hold architectural coherence across thousands of lines. i ran it five times. multi file, single file, thinking mode on. broken imports, blank screens, skeleton code that never rendered a single frame. on the same 3090 qwen's 9B dense built 2,699 lines and was playable on its first iteration. cascade 2 at 3B active never got there. 3 billion active parameters winning gold at the international math olympiad is real. but math competitions and autonomous coding are different problems. the speed is there. the reasoning is there for structured tasks. but holding coherence across thousands of lines of game logic, particle systems, audio, and collision detection? 3B active MoE hits a ceiling. cascade 2 is the fastest local model i've tested in its class. for complex agentic coding it's not ready at this size. test before you commit.


- Drafted a blog post - Used an LLM to meticulously improve the argument over 4 hours. - Wow, feeling great, it’s so convincing! - Fun idea let’s ask it to argue the opposite. - LLM demolishes the entire argument and convinces me that the opposite is in fact true. - lol The LLMs may elicit an opinion when asked but are extremely competent in arguing almost any direction. This is actually super useful as a tool for forming your own opinions, just make sure to ask different directions and be careful with the sycophancy.


GLM-5.1 is available to ALL GLM Coding Plan users! z.ai/subscribe












