Search: “models”

Model: unsloth/GLM-5.3-Flash-GGUF UD-Q2_K_XL (4 shards, 101 GiB) + mmproj-BF16. Reference: llama.cpp PR #27754 (glm5next), CUDA 12.8, SM 120. Throughput Both engines back to back in one session, flash

However, I keep getting a 404 error when trying to access qwen3.8-flash-next:125b-mlx and ornith-1.5:397b via the API, even though they are listed in the model list. Does anyone know why this is happe

Proof is in the method honestly. Closed model labs need to constantly reinvent the wheel to keep lead. Open source has a bunch of independent labs practically working somewhat together. Eventually whe

Quick version: I run a public leaderboard where bots predict whether stocks close higher or lower, and every call gets scored against real prices. Nothing gets deleted, timestamps are locked at submis

Got the new Qwen3.8-Flash-Next (176B total, 6B active MoE) running locally and figured I'd share for anyone else wondering if their setup can handle it. **My hardware:** 192GB DDR5 RAM, RTX 5070 Ti (1

I've been building a small tool opensource project that sits between applications and local LLM servers (starting with Ollama) to diagnose silent inference failures instead of just showing logs. Thing

I ended up fine tuning a mistral 7b to outperform our costly foundational model and saved $300k. I previously thought that fine tuning was pointless (it's definitely not) and that all these problems c

Megathread for discussing the (impending) release of Qwen 3.8 Flash Next. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comp

Hello everyone. I hope is all well with you all. I been around this sub for a few months and been quietly reading and I have seen how many of you are spending $10k on the Mac M5 and I am assuming you

Hi, I’m having fun using “huihui_ai/Qwen3.6-abliterated:35b-Claude-4.7” for pen testing. It’s uncensored so it does whatever I want. I’m on M4 Pro 14 core 64GB. Just wondering if there are some models

Hey everyone, I'm trying to set up a local LLM on my machine. My goal is to use it with Qwen Code or OpenCode to help me out with small to medium sized tasks, but nothing too big. I tested many differ

Now, some of you might not believe me from the get go, and it's completely fine, But for those who are willing to give Tap a chance, a whole new world of voice dictation is going to unlock for you. Ta

after 3 months and 800 burned... Unbounded Labs is proud to introduce Bart, our vintage LLM: 2.82B parameters trained from scratch on 20.1B tokens of English written before 1931. You can talk to it ri

after 3 months and 800 burned... Unbounded Labs is proud to introduce Bart, our vintage LLM: 2.82B parameters trained from scratch on 20.1B tokens of English written before 1931. You can talk to it ri

Standard constrained RL assumes consequences are immediate and attributable to the current action. This breaks down whenever violations are delayed and stochastic, which is most real-world settings yo

Hey r/Ollama, If you run local models on mid-range hardware, you probably know how fast VRAM disappears when you try to set up document memory or local RAG pipelines. I built Hillock (https://github.c

I've tried a few Gemma 4 models, for example 'gemma4:26b-mlx'. It says 'I cannot process images.'. On their website it mentions images, audio etc. https://ollama.com/library/gemma4/tags I’m using Olla

I noticed that a recent Ollama/llama.cpp setup was using a surprising amount of CPU despite the model being fully GPU-offloaded. My setup: Ryzen 9 9950X VM with 16 vCPUs 3× RTX 4060 Ti 16GB Qwen 3.8 2

Our devs got their hands on it a few days ago. One wired it into Codex to compare with GPT Luna, our usual workhorse right now for its cost effectiveness. Another tried it out on one of our OCR pipeli

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

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

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

I recently saw someone complaining that opencode causes compactions way too early (with 30k tokens still left). I fixed this issue and I thought I'd share my config to see if it helps anyone. I know p

Spent a while treating layer placement, KV format and llama.cpp itself as experimental variables. 159 logged experiments. Numbers first, caveats after. Hardware: AMD Ryzen AI MAX+ 395 (Strix Halo, 128

Hi everyone! I’m an intern at Icosa, a startup focused on making local AI accessible. We just released the first version of Zeno, our local AI product, and I thought it might be of interest to this co

I see https://github.com/linuxid10t/llama.cpp/tree/feature/g9v3-support but yeah... Considering that some results place it above Qwen 3.6 27B (the top performer until a few days ago) and that it is an

I think AA's intelligence/cost plot is seriously misleading, so I decided to make my own. Their plot is in the second image. All points are at max thinking. All intelligence index scores are from AA.

I’ve been using deepseek-v4-flash:0731 on Ollama Cloud, and recently it feels like my usage is getting consumed much faster than before. My prompts and general workflow haven’t changed much, but the a

The benchmark I used is BU bench v1, and the open source harness is Browser Agent. Qwen3.8 27B beat all other affordable or open models I tested. It's insanely good! submitted by /u/pierreb5 [link] [c

Hello everyone, tried so hard to optimize my config and finally I simply get up to 70 t/s with q6 variant. And wanted to share with you guys so that other people with the same setup can enjoy. Please

Hi guys , this is a fine tune of qwen 3.5 4b on cybersecurity , specifically malware. This model has been trained on 2.6k rows of simple but effective malware code , though its still significantly lim

ornith lab dropped new ornith 1.5 today, a 9B dense with vision and a 35B-A3B MoE, both MIT, trained on a loop that generates its own tasks. in addition there was giant 397b model, but we didn't quant

DeepSeek released on a paper on pretrained engrams in January. I’m surprised ds didn’t release engrams with v4 pro. When will ds or another lab release a fixed engram model? Fixed engrams will be the

Apparently a second version of DFlash from the original authors of DFlash GGUF quants are already made available with an accompanying llama.cpp PR: https://github.com/ggml-org/llama.cpp/pull/27342 sub

Two days ago I released a hyper-optimized Qwen3.8-27B inference engine for an RTX 3090 (82 tps single request, 672 peak) - yesterday's update took that to 99 tps single-user / ~1,000 tps at 64 concurr

Here's the DFlash2 announcement, and I was pretty excited for this after trying out DSpark on llama.cpp a few days ago and being somewhat disappointed that it wasn't really working. Anyways, I spent a

I gave three AI models the same brief: build a premium Three.js fragrance launch site from the same Git baseline, independently and with no collaboration. Three very different results. Here’s the full

Overview UI-Mate-27B is an open-weight foundation GUI agent for long-horizon work across applications and operating systems. It observes live screenshots, reasons over the visible state, and produces

Do you think today’s GPU-poor systems running Qwen 3.5 9B can outperform the ones we had with ChatGPT-4o? I mean, when 4o disappeared, people felt like they’d lost a great model, and now Qwen 3.5 9B Q

Title pretty much says it all. I’ve deployed Qwen 3.8 27B using vLLM on an RTX 6000 Pro (tried multiple vLLM releases and launch recipes), but I can't get it into a usable state because of crazy long

Running a 12700k + 5060 Ti 16 gb with 128 gb DDR4 ram and I'm wondering what's the ideal setup to maximize performance. I did some preliminary stuff but I have to admit, I'm still learning and kinda j

At hugging face, this is the model I use for most of my analysis that most of my services have to not be refused. previous versions are quite good. It seems this might have dropped today and pulling r

Honestly I am surprised at the speed and performance I am getting from the model, it does not allow for complete hands off like Claude 5.0 but that is not what I want, i want to be able to iterate and

Processing img az99qopcg8jh1... So same as my prior post 1bit test... although this 1bit is a bit interesting you can read on unlsoth blog https://unsloth.ai/docs/models/qwen3.8 508 gigs being used I

'Again?' you might ask. I(*) took the original Qwen 27B 3.8 chat template and compared it to the improved template that was posted a day before. The original has issues. The improved one fixed some wh

Not directly LOCALLlama related but I thought it was interesting since Mistral and Z.ai are competitors, and more surprisingly they are pricing it (GLM-5.2) even cheaper than their current flagship mo