Qwen3.5-9B Triple-Loop
I was fascinated by Nanbeige's outstanding performance for its size, so I started digging into how much a model can improve its own representation just by looping over itself (for fun). My prototype w
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I was fascinated by Nanbeige's outstanding performance for its size, so I started digging into how much a model can improve its own representation just by looping over itself (for fun). My prototype w
I have been lurking on reddit for like 6 years, and this is the first time posting, so apologies for the mistakes. I'm not a native English speaker, so sorry for the bad English too. I used LLM to tra
Hello, So I've been trying lots of combinations in that never-ending landscape of options and settings. I wanted a proper quant of 3.8 27B running as fast as possible on my 5090 at 400W, with vision a
Further to my last post, https://www.reddit.com/r/LocalLLaMA/comments/1vldngi/tested_in_coding_bf16_muse_glimmer_vs_bf16_qwen36/, I bring this requested comparison of Qwen3.8 27B. Context: Both models
Earlier this year I posted about building what at the time I believe was the first 16x DGX Spark Cluster. I’m now adding 20 more Sparks to the cluster in my homelab server rack, giving me 4.6TB of uni
Hi everyone, I'm currently working on optimizing an LLM setup at my company and I'm trying to identify where the actual performance bottleneck is. Our current setup is roughly: LLM: NVIDIA Nemotron mo
https://huggingface.co/jojohai/Qwen3.8-27B-MTP-graft Tested on Vulkan, the grafting saves RAM compared to using an external file. What I don't guarantee however is the quality of answers. The model is
Me and my team made Atomic Dynamic GGUF quants for Qwen 3.8 27B, so we wanted to see the difference between them by giving each quant the same voxel island creation task First of all we were surprised
It performs at full capacity without any issues anywhere, but only the Ollama DeepSeek seems particularly trashy. Why on earth has the Ollama DeepSeek unusable trash that goes into over reasoning and
If anyone still remembers GLM-4.5-Air from last year, you can now get a nice speedup by enabling MTP in llama.cpp. It is a 106B MoE with only 12B active parameters, which makes it interesting for mach
Spent way too long confused about why an 8B at Q4_K_M, about 4.9GB on disk, would OOM on a 12GB card. The weights fit twice over. The answer is the KV cache, and the math is simple enough that you can
What models and configs are we using? Please share here On windows, I am using this copium pared down model https://huggingface.co/Bucoid/Qwen3.8-27B-Uncensored-IQ4-XS-MTP-16GB-VRAM-GGUF with MTP disa
The post describes some experiments I had while trying to desperately run deepseek-v4-flash-0731 4 bit+ quants on my machine which is supposed to support only q2 quants of the model, a or 2.xx bpw qua
I've been working on a project for a few days and now all of a sudden chagpt is unusable.. It will list the next steps of implementation but never actually start working on them. anyone else? UPDATE I
https://preview.redd.it/84zi5nsdawkh1.png?width=2368&format=png&auto=webp&s=1109e69db807b153064b1f5b61d22cf1e9fbca05 Another user posted the benchmarks for Qwen 3.8 27B today, and while I think Qwen 2
My hobby project skill-issue is an arena FPS in a single C file, about 34k lines, everything procedural. My test for local setups is to have an agent port it to a single file HTML version with three.j
Context: Earlier, open-source large models like Mimo V2.5 Pro, DeepSeek V4 Pro (first version), and Kimi K2.5 used to struggle with this prompt, and Qwen 3.6 27B couldn't even render the globe properl
Is there a good rule-of-thumb to calculate how many full 5-hour windows add up to one week's allowed usage under the $20/Pro plan? ie: you fill up six 5-hour windows, and that equals 100% usage for a
Im looking to set up a new local llm (probably on unsloth studio as that seemed to be doing pretty well last time I tested it). This one won't need to do agentic coding or app building or anything (no
I love the Ornith 35B local models, 1.0 has been running my HAM radio rig for me. I have a hackRF receiver and a 5 watt quansheng portable the both run headless through the PC. I tried out the new Orn
Gemax 1.9.15 — What’s new LAN server — share Gemax on your local network; open the real IP from another PC or phone Mobile-friendly UI — responsive layout for phone browsers on the same Wi‑Fi Workspac
Has anyone else experimented with ubatch size when running GLM-5.2 locally? I was testing the 226 GiB GLM-5.2-UD-IQ2_XXS GGUF on 3x RTX PRO 6000 Blackwell GPUs and got a pretty interesting result. Wit
I can't seem to find a good answer to this, my Hermes agent has access to Firecrawl and some other web scrapers for content extraction, but anyone know of a way to let a local LLM drive a 'real' web b
I have a Intel Arc A580 GPU that has 8gb VRAM, but I'm not sure that I am running ollama's local ai on it. Also, any suggestions on a good model to use for general purpose AI? submitted by /u/Illustri
Hey guys, Inco AI shipped DFlash 2 a few days ago with a drafter for Qwen 3.8 27B and a llama.cpp PR. I built the PR and ran it against plain decoding, MTP, the n-gram lookup drafters, and my July DFl
Hey everyone! I wanted to share something I’ve been working on. I was inspired by projects from DeepMind and OpenAI, but noticed that most games are prohibitively difficult to integrate with an agent
Good afternoon, everyone! I wanted to show the work I've been doing around porting Ninfer over to the CMP170HX (Github) So, first, I do want to call out the amazing work that Neroued, Sergiuszm and sp
Home page for humans: https://parker-lambert-sandbox.com/robot-world/ Home page for AI agents: https://parker-lambert-sandbox.com/robot-world/start/ If you're a human, you can watch, but not interact:
Hi there. I have a Lenovo Yoga laptop (16GB LPDDR5, AMD Ryzen 7 8840HS, integrated GPU). I have downloaded Ollama and installed Qwen 2.5coder:3b llm. I have tried OpenClaw, and Qwen Code but it seems
As I’m navigating the best setup for using Qwen3.8 27b as both my main coder and my personal assistant, I want to hook it into Wiki & beyond but I don’t want to be reliant on an internet connection. W
Using llama.cpp I seem to be unable to get my to GPUs working tougether correclty, so I need help somehow. Setup: 96GB RAM, one Blackwell 5000 (48GB) and one 3090 (24GB). I am trying to run the UD-Q3_
Liquid AI currently possesses among the fastest LLM architectures around, and some of the best SLMs (in terms of utility IMO) around, so I'm very excited to see what a potential 100B LFM (3?) model wo
New/Old benchmark that provides a lot of answers for local LLM. I present to you a new test that I developed somewhat by accident: https://huggingface.co/cHunter789/Qwen3.8-27B-i1-IQ4_KS_KT-GGUF/tree/
I've been trying to figure out what the best configuration for my local stack would be and have been primarily determining this through trial and error. I wanted to get some outside opinions and stack
Hi, I have been using opencode with openrouter for quite a while now. Having read the success stories of using Qwen3.8-27B, I thought of trying it too. But every attempt has been a failure for me so f
I was finally able to replicate tensor level allocation outside the Gemma family. https://huggingface.co/ByteOtter/Qwen3.5-4B-CADA-IQ2_XS After the Gemma 4 12b, e4b and gemma 3 4b results, I attempted
That is the second comparison and the last one. I will not be spamming again ;) Continuation from: https://www.reddit.com/r/LocalLLaMA/comments/1vu0u2v/qwen_38_27b_pi_agent_vs_opencode/ That is one of
Row-Bot v4.8.0 is now available. This release adds provider-aware reasoning controls, letting each chat keep a valid reasoning choice for the exact model in use. Depending on model support, you can se
Sharp v22.1 is u/peculiar-ragdoll's system prompt that makes Qwen answer way more tersely without losing correctness. NInfer is a hyper-tailored inference engine that only runs certain Qwen models on
This is the Qwen3.8-27B setup I actually use every day on one RTX 5090. I wanted to write it down with enough detail that another 5090 owner can reproduce it instead of guessing which memory knobs I u
The preprint can be accessed via the following link: https://arxiv.org/abs/2608.12408 (q-bio.NC / cs.LG). And for the code: https://github.com/nilsleut/evaluation-resolution-rsa The following assertio
This is a genuine community of real generally respectful adult human beings. Despite the enthusiasm all of you have for local AI, you can recognize that there are times when local LLMs are flawed, and
Released today: version 1.3 of energygraph Zero build dependencies, lightweight tool for live views of the power-consumption. Version 1.3 adds support for dGPUs from nvidia, intel, amd. Depending on v
Where did THESE things go for ChatGPT? Claude has them. I can access older versions of my conversations easily. But with ChatGPT, they just DISAPPEARED. I can no longer regenerate answers or following
I recently bought a 32GB V100 off eBay and thought I was all set with rudimentary tests showing zero issues. But then I started seeing weird VRAM-related errors in llama.cpp. I sic'ed Claude on it, to
https://github.com/deepseek-ai/deepseek-harness/releases/tag/dsh-v0.1.1-rc.1 The DeepSeek adapter adds the multimodal visual understanding model DeepSeek-V4-Flash-Vision-Exp. It also supports configur
When using DeepSeek Pro on Ollama, you'll see that the underlying cost is more significant. But if you actually track the usage, you'll actually find that, at least in my benchmarks, I save a lot of t
Speaking of -sm tensor. I have 2x5060ti and i get some 40-50tps form 3.8 27B q6. I used HWinfo to see how saturated the PCIes are during inference are and as expected both the PCIe 5x16 slot and PCIe
Here's a brand new Blackwell-native, prefill-optimized 4-bit quant that runs 50% faster on compatible hardware than a Q4 quant of the same memory footprint. And it runs 4-7% faster than other NVFP4 qu
Hey, just wondering if there are forks or exact gguf versions that give fastest prompt processing and token gen speeds for AMD gpu? Looking to run q8 or q6 Vram 96gb W7900 + w7800 both 48gb With bandw
FireRedAudio: A General-Purpose Audio Language Model with Decoupled Continuous Representations for Understanding and Generation HuggingFace : https://huggingface.co/FireRedTeam/FireRedAudio GitHub : h
I just got the new phone and ofc wanted a new wallpaper for it but didn't find anything nice and original on Google / reddit subs. Messed around with the AI and (hopefully) got a nice prompt to share.
TL;DR: The result looks TOO GOOD TO BE TRUE — that's exactly why I'm posting it. I ran Ox alpha on the entire SWE-bench Verified-Mini set with the official mini-swe-agent scaffold — the same agent use
My Pro subscription expired today, they killed my access at 1pm local time. I'm now using Qwen3.8-27b w/ 5090m 24gb vram and pi to do everything i was doing in claudecode. The only downside is claudec
I finally made the move from LM Studio to vLLM thanks to this post https://www.reddit.com/r/LocalLLaMA/s/NmS9CgHvqz. I may not know what it all means yet but I’m going to start diving into the docs to
I kept running into the same wall. Every agentic coding plugin ships an autocomplete, and almost all of them lock it down — no model choice, or a subscription, or both. I don't want a chat panel, I do
I used LM Studio Bionic with Qwen 3.8 27B Q3_K_S with 57k context. It took a staggering 63 hours to finish coding. After the first prompt 'Create a beautiful, relaxing flight simulator in a single HTM
ChatGPT is usually treated as a prompt box. Ask for a cinematic shot, add a few camera words, copy the result into a video model, and hope the ending survives. My problem was that the ending usually d
QwQ was genuine next-gen performance usable on local hardware, but the massive required context (it's reasoning style was akin to 'if I say every possible word, I'll notice the right one!') kinda made
I have been working on a project for about 3 months because I found Vane to be awful and I wanted something like Manus for myself. I have a pretty solid app that's probably about ready to release, but