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model roundup

Qwen 3.6

50 items · started 2026-06-05 · closed 2026-06-16

  1. * AI CODE CREATION GitHub Copilot Write better code with AI GitHub Copilot app Direct agents from issue to merge MCP Registry New Integrate external tools DEVELOPER WORKFLOWS Actions Automate any workflow Codespaces Instant dev environment…

  2. RTX 5080 + RTX 3090 Setup: 80+ Tok/s on Qwen 3.6 27B Q8 A year ago, I bought an RTX 5080 for both gaming and AI experiments. Little did I know back then that I would be giving into the joys of local LLM setups.

  3. How to Setup a Local Coding Agent on macOS Running Gemma 4 26B-A4B and Qwen3.6 35B-A3B locally with llama.cpp, MTP speculative decoding, multimodal support, and PI as a coding agent. I'd had my internet fail a few times recently leaving me…

  4. Hello everyone, i had a 3080ti 12gb and added a 3080 20gb, so it has a bit less speed but more memory than my main card. I could finally get some speed with the usual suspects (i am testing gemma 4 31b/26b-a4b and qwen 3.6 27b/35b-a3b), BU…

  5. 06 — Air-Gapped Claude Code¶ The setup, the fixes that make it work, and the hardware that sets the pace Claude Code connects to a model running locally on the laptop. You provide a Kubernetes incident for investigation.

  6. I've been experimenting a bit today with letting models reason for creative tasks, rationale being that it might help with keeping track of details and prompt adherence. And predictably, the wall I'm running into is that they all want to d…

  7. If Gemma 4 is better, does anyone have a link for the latest fixed template? Using LMstudio.

  8. TLDR; I only got a 6% improvement on tokens/sec over naïve parameters. I was messing around and ran a hyperparameter search with optuna over the MTP and speculative decoding options of llama-server for Qwen3.6 27b on strix halo.

  9. I'm running Qwen 3.6 35B-A3B via Pi harness on a 32gb unified RAM setup (Framework 13). llama.cpp, 64k context window.

  10. There's a post i saw about Claude Fable where a user asked the model the car wash question and it sent me down a rabbit hole. I spun up qwen on llama.cpp and in the llama.cpp chat interface I asked the model and it got it right consistentl…

  11. Hello i'm running the qwen 3.6 27b in ud q5k xl, and with all the optimizations it barely fits in my 3090 vram with a 120k context, i'm sure it does not spill when context is full but i would like to improve the token generation speed. I w…

  12. Deploy an Agentic RAG powered by Alibaba’s latest Qwen 3.6, running fully on your machine.

  13. Hey everyone, I'm running Qwen3.6-MTP-27B-MTP (Q4_K_M) with llama.cpp server on a Tesla V100, and I'm currently getting around 55 tokens/sec. I'm trying to find out whether there are any configuration changes that could increase throughput…

  14. I have always been a fan of the AutoRound quants of this model, for some reason, it thinks less (sort of like Qwopus models) and comes up with solutions quicker than Unsloth quants for instance. https://huggingface.co/sphaela/Qwen3.6-27B-A…

  15. I see a lot of conflict comments on this sub and elsewhere on how useful is qwopus compared to for example unsloth quants of qwen3.6 27b. Some say it’s worse some say it’s much better.

  16. I’m trying to test Qwen3.6-27B for agentic coding through Cline / llama.cpp, but my local box struggles once the context gets longer. (my poor 3080 just can't keep up).

  17. What are the best models, quants and llama.cpp versions/forks for CPU inference these days? I have AVX2 but no AVX512 - Intel core ultra 7 165H; 64G RAM This seems to ask for massive MoE (a lot of RAM, not a lot of bandwidth/compute).

  18. Hey everyone. I'm brand new to running LLMs in general, even more new to running them locally, and the sheer number of tools available is absolutely overwhelming.

  20. I had a huge LLM server, and now I have a tiny one! I had a Jetson Orin NX gathering dust from a long dead robotics project, from back in the Llama-7B days.

  21. I'm just getting started using local LLMs for code. I'm not interested vibe coding, but I am hoping to increase my productivity in the publish or perish world of academia.

  22. Hi, totally new to using LLMs for coding purposes, I am on Ubuntu and currently using LM Studio with Qwen 3.6 27B Q4 on a 5090. Finding it slow and context runs out fast.

  23. Right now, I am running llama.cpp on a M2 ultra 64gig. Having great fun with unsloth/Qwen3.6-35B-A3B-GGUF:UD-Q8_K_XL - Running opencode and finding it amazing to have such great tools running locally.

  24. Forgive the claude summary, in the readme, but the base works. I'm still working on the hip kernal and having it combine with MTP.

  25. I've previously posted some small performance benchmarks, but this time I got interested in the qualitative side. u/Substantial_Step_351 posted a few days ago about why models are not benchmarked on tool calling, and u/complexminded pointe…

  27. These last few weeks have been godsend for 24GB (and below) gpu poor peeps. Killer models released (Gemma 4 / Qwen 3.6) Free intelligence via QAT Bonus speed via MTP We're at the tipping point where GPU poor (24gb and below) people are act…

  28. Hardware: RTX 5090 | Model: Qwen3.6-27B | Framework: BeeLlama.cpp Full benchmark scripts, raw data, config, and generated artifacts are available on request — just DM or comment below. I spent the last week benchmarking DFlash speculative…

  29. Single steam benchmarks (club-3090) model: qwen3.6-27b-autoround-int4 BEFORE: 1x3090 *Their default script recipe for single 3090'*s (4-bit quant and 4-bit kv cache, mtp=2) NARRATIVE decode_TPS: mean = 53 std = 0.6 CODE decode_TPS: mean =…

  30. Local LLMs are great, in fact lots of simpler things like a fastapi web server they can do quite well. The moment you move outside of that - things get a bit worse.

  31. It’s finally here! Something many of us running dual RTX 3090 rigs have been anticipating.

  32. Where I came across it: https://www.reddit.com/r/LocalLLaMA/comments/1txxgpq/openlumara_a_different_kind_of_ai_agent_written/ DISCLAIMER: A good posting would be: This is what I wanted to do with Lumara. Here is what worked, here is what d…

  33. Realtime check X for new people to follow I have been pretty pessimistic about local models for agentic workflows for a while. Not because they were useless, but because in practice they often felt just a bit too slow, too fragile, or too…

  34. The cost of training is coming down. We have incredible open source models (especially smaller ones) like qwen 3.6-27b.

  35. Hi, so I have a pretty low-end laptop regarding running LLMs locally (NVIDIA GeForce RTX 3050 with 4GB VRAM, AMD Ryzen 7 5800H and 16GB DDR4) and while I'm not looking for anything to realistically work with, I'd be interested in how could…

  36. Full benchmark results and in-depth analysis are available in the articles: KV Cache Quantization Benchmarks for Long Context and KVarN KV Cache: Implementation and Benchmarks. BeeLlama.cpp (my llama.cpp fork) was used as inference engine…

  37. Hi folks, I found this setup on consummer hardware that seems to have great results on local hardware. - qwen 3.6 q6 - 450 K context using turboquant turbo3 mode llama.cpp fork - multimodal support This AI generated blog article is a kind…

  38. Just received an RTX 6000 PRO, and I have an 5090 Astral. I am considering running a Qwen 3.6 27B on the 5090 and maybe two or three more on the 6000 to play roles such as lead SWE and coder and researcher.

  39. Just kidding. Are there any distills that actually improve a model's quality?

  40. My goal: I want to use an LLM to learn more about software/firmware reverse engineering and binary analysis. Eventually I would like to learn how to build agents to augment parts of this process.

  41. I've been happily using GitHub Copilot for 7-8 months, primarily in Visual Studio and VS Code, mostly with the built-in flagship models and have felt like the output is worth the cost. Lately I've been playing with a lot of different local…

  42. First we never saw an upgraded Air model after 4.5. Then GLM 4.7 Turbo was great, but quickly surpassed for coding.

  43. I’m a web developer doing mostly coding, but also project management, requirements analysis, testing, etc. I recently started experimenting with local LLMs, mostly because agentic stuff finally made them feel useful.

  44. So long story short - openai 20$ subscription is much better than my local AI stack… r7900xtx+32GB RAM (Qwen3.6-35B_Q4+OpenWebUI+SerXNG+Playwright+opencode). I wasn’t expecting much but it’s literally impossible to replace chatGPT level of…

  45. I have a 5090 power limited to 475W. When I run the following command, it barely hits 300W and I get something like 30 t/s: bash ./llama-server \ -m ~/myp/models/unsloth_mtp_Qwen3.6-27B-UD-Q5_K_XL.gguf \ --host 0.0.0.0 \ --port 8080 \ --ch…

  46. Hey r/LocalLLaMA, Before anyone jumps on me, this is absolutely not a post about how great Qwen is 😄 Even though I use Qwen 3.6 35B-A3B daily, I’ve found a massive gap between Opus and every other model, local or frontier (including GPT 5)…

  47. I’ve been doing lots of testing back and forth with this 7900xtx. All of my workloads were relying on qwen3.6 models, which are amazing fwiw, but I wanted some diversity in thought.

  48. TL;DR: I spent a long session tuning a 35B MoE on a tiny 8GB laptop GPU. Three things mattered a lot (--no-mmap, VRAM headroom, closing CPU-hungry apps).

  49. How different are the image recognition capabilities between gemma4 and qwen3.6? I give the model the task to extract calendar events from a photo of an calendar that is croped to the calendar.

  50. So, llama.cpp has the -nkvo (--no-kv-offload) option to offload KV cache to RAM instead of VRAM. Many people avoid this because obviously it hurts performance.

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