d4mations

@ivanfioravanti @Apple Not so sure 4bit is really useful day to day. For benchmaxxing ok but for real world use, I would prefer 8 or worst case 6bit

1/3 MLX Context Benchmark of Qwen3.5-27B-4bit on M5 Max 128GB. Strong model and good speed overall! @Apple M5 Ultra will be a beast!

@JamesNumb3rs @_weiping Hhhmmmm I’m on mlx_lm on mac with an mlx 8bit quant and opencode desktop. Wonder if there is something in that stack that’s not helping

@d4mations @_weiping worked fine for me opencode llama.cpp amd 9070 16gb + spillover ddr5. went to plan mode. asked it to build an amiga demo, rotating cube, painters' algorhythm. then build mode. did it. 50tks write 400tks prompt processing

🚀 Introducing Nemotron-Cascade 2 🚀 Just 3 months after Nemotron-Cascade 1, we’re releasing Nemotron-Cascade 2: an open 30B MoE with 3B active parameters, delivering best-in-class reasoning and strong agentic capabilities. 🥇 Gold Medal-level performance on IMO 2025, IOI 2025, and ICPC World Finals 2025: • Capabilities once thought achievable only by frontier proprietary models (e.g. Gemini Deep Think) or frontier-scale open models (i.e. DeepSeek-V3.2-Speciale-671B-A37B). • Remarkably high intelligence density with 20× fewer parameters. 🏆 Best-in-class across math, code reasoning, alignment, and instruction following: • Outperforms the latest Qwen3.5-35B-A3B (2026-02-24) and even larger Qwen3.5-122B-A10B (2026-03-11). 🧠 Powered by Cascade RL + multi-domain on-policy distillation: • Significantly expand Cascade RL across a much broader range of reasoning and agentic domains than Nemotron-Cascade 1, while distilling from the strongest intermediate teacher models throughout training to recover regressions and sustain gains. 🤗 Model + SFT + RL data: 👉 huggingface.co/collections/nv… 📄 Technical report: 👉 research.nvidia.com/labs/nemotron/…

@daniel_mac8 Really good performance but tool calling is broken in opencode. Cascade 2 is completely unusable

Nvidia released Nemotron-Cascade 2. A 30B-A3 MoE open model on par with Kimi K2.5 on LiveCodeBench. It achieved IMO gold level!

@drmarlonperalta Lilly is studying dosis up to 25mg of tirzepatide

Impressive. Let’s nuke our GLP-1 receptors. What’s the highest dose of semaglutide you’ve tried?

@iMilnb I get 50+ on an m1 64gb at 8bit. It’s just not that great of a model. It gets stuck in a tool calling loop that it can’t get out of

Epic Reddit post on running Qwen3.5 35B q4 on a 16GB RTX 5080 at 75 tp/s! reddit.com/r/LocalLLaMA/s…

@gregogallagher This isn’t even a perception debate, it’s a matter of the composition of both peps. Tirz will have more suppression for the same dose as reta as it contains more glp1 than reta.

Some claim Reta suppresses appetite better. Others claim the exact opposite, Tirzep suppresses hunger better. Which is it?

@MichaelMindrum And use all three regularly

@MichaelMindrum I have both and a hotmail for good luck

I am moving from aol to yahoo for email. Seems like a much better model.

@rorynotsorry @ElevateBiohack Tirz for sure

Man, I want to do a poll. The answer is obviously Retatrutide, but I’m interested is all of your wrong answers. For instance @ElevateBiohack says Tirzepatide.

@codeRunnerUK @TommyFalkowski Yeah I agree, once the context grows it becomes flaky at best and at worst it’s starts looping like mad

@TommyFalkowski I found it to be hit-and-miss on my long context coherence test. Now that I've started testing non-Qwen3.5 models, it's showing how good Qwen3.5 is, but it's definitely a "your mileage may vary" model at 35B-A3B long context.

qwen3.5 35B-3A can actually do stuff. It's so weird and awesome to see a local model do useful things. Even with a pretty full context window it still seems usable.

@DigitalFringed1 Undeco, cypio, ??

After about 6 weeks back on a 100mg TRT maintenance dose following my first tiny cycle, I feel perfect, exactly like my old self. Less variables & pinning is nice as well. I'm staying here long-term. The only addition I'll make is MT2, that stuff just works.

@Gabri3lTheGreat Yeah, me. Am doing both at the moment and its great!

has anyone actually stacked tirz & reta before

@peer_rich I’m looking for a peptide that’ll take that urge away!!!! I’m desperate!!

the male urge to build a GPU cluster at home

@Clark10x Haha this the first polymarket post I believe!!!

I've spent about 3 weeks and over $2,000 in Claude tokens setting up multiple agents to trade on Polymarket It was paper trading for a week and averaged about $80 per day It's been live for 2 days & completely broken All of these other people gotta lying on the timeline 😂😂

@Pawzgm @wildmindai If and when it stops the thinking loop

@wildmindai GLM is trash. Get a second-hand 3090 24GB for $1,000 and run Qwen3.5 27B, which is almost the same as GPT 5.2 and a bit worse than Opus.

Hot! you don’t need a $5k GPU to run a 30B model dev drops a custom Linux module, claims GLM-4.7-Flash model run smoothly on RTX 5070 with 12GB VRAM - normal PC RAM pretends to be VRAM - bypasses the CPU completely - inference speeds actually stay fast But... wait, don't we already have offloading? gitlab.com/IsolatedOctopi…

@Sergizzzz4 @LottoLabs I’m running 8bit on the same mac as you. It’s 11-12 tokens/s

@LottoLabs What model of qwen 3.5 27b can I run on my Macbook M1 Max 64GB properly? Thank you ser

Essentials/ 3090 > qwen 3.5 27b > hermes agent > tailscale

@sudoingX Did the migration last night but encountered bug with custom/local llm that would not use the correct api key

i get this question a lot recently so let me be clear. hermes has 11 model specific tool call parsers built in. it knows how qwen, deepseek, llama, mistral format their tool calls natively. openclaw doesn't parse any of that. it expects the API to handle it. that's why my 9B on a 3060 never drops a tool call through hermes. every single tool call lands clean because the parser understands the model's format not just the API spec. the openclaw founder joined openai in february and the project got handed to a foundation. hermes is built and maintained by nousresearch, an independent research lab that ships open source models and tools for the community. you decide who you want holding your agent framework. if you're on openclaw right now hermes already has a migration script built in. i'll help anyone who wants to make the switch.

@Teknium I think I found a bug in how hermes handles local/custom providers. Seems not to get the api key right or doesn’t send the right api key. Will investigate a bit more and send a PR

Lots of documentation updates today, added a search bar too, check it out! hermes-agent.nousresearch.com/docs/

@devindolar @nix_eth Theres a new omlx reddit group r/omlx

@nix_eth Have you tried Qwen3.5-27B dense? I've bought the same Mac. So excited to receive it! What system are you using? oMLX?

LLM speed on my MacBook M5 Max (128GB): • Qwen3.5-35B-A3B (Q6): 74 tok/s • Nemotron-3 Super (Q4): 24 tok/s • Qwen3-Coder-Next (6-bit): 67 tok/s • Llama 3.3 8B Instruct (Q4): 99 tok/s On my M1, Llama 3.3 was my go-to for most local tasks at about 20 tok/s. On the M5 Max, it's hitting 99 tok/s. Qwen3.5 feels like a huge upgrade and is my favorite so far. Qwen3-Coder-Next is surprisingly good at dev tasks, although I'll probably stick with GPT-5.4 for most. I'm also impressed by Nemotron-3 Super, but its personality feels a bit too dry.