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European 78B A3.4B model is now supported by llama.cpp, I am waiting for some GGUFs https://huggingface.co/Aleph-Alpha/Kolibri-1 Kolibri is Aleph Alpha's mixture-of-experts (MoE) reasoning model, with a focus on German and English. The model supports an explicit reasoning mode and tool calling
I've got some nice boost by increasing --adapt-every value from calibrated 1 to 6. I tested on 4 consecutive prompts(Slovak language) in chat. Prompt 1-3 are simple questions, 4. is describing source code(20K tokens) Results: [prompt number / ~avg. output length] UD-Q4_K_XL: [1 / 996] 30.3 -> 36.1 t
Existing weights are untouched Interacting with models via API calls is outside the scope of these controls 💢 Next-gen Chinese frontier models may face licensing requirements, export registration, delays before weights can be downloaded abroad --- Essentially it creates regulatory mechanisms for B
Defiance puts DavidAU's Turbo-Brilliance "AI Construct" modes on HauhauCS's uncensored Qwen3.8-27B. You pick a mode (Joker, Dr. House, a 20-agent Einstein panel, a Socratic tutor) per request, and the uncensored weights answer it without hedging. Weights: HauhauCS/Qwen3.8-27B-Uncensored-Hauha
Was waiting for this. Edit: And it just dropped: https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017 submitted by /u/chemist_slime [link] [comments]
I use Pi/OpenCode for coding tasks which still seems to be the most popular, but I'm wondering what you guys use for normal chat interface. It's been a few months since I've seen discussions about harness and at the time the popular non-coding choices seem to be: - OpenWebUI for general use - Silly
My experience is based on running Qwen 3.8 Flash Next UD-Q4_K_XL on 4x 3090's Compared directly to Qwen 3.8 27b Q8 it is not even close. To add to this, strata results were even worse than llama.cpp even thought generation speeds were faster. I left 1 run for 4 hours in strata and it did not p
I know everyone's excited about 3.8, but honestly I'm still refining 3.6. And I hate the way 3.8 talks, so... I keep seeing all these posts about what's the use of open source, so I figured I'd submit my own answer with this post. Qwen 3.5 27B was my first agent, starting my journey around M
Tracked my first run of MiMo Pro on a Jetson AGX Thor at a scorching 0.646 tokens/sec,.. but it DID technically load and run, so it counts. Every decoder layer, routed expert, SSD read (..a good bit more) traced and replayable step by step. Here we can't what-now?.. it's ~566GB of model (FP8
K3 came out in July hyped as the best open model you could download, and it scored 57 on Artificial Analysis, right up there with Opus 4.8 and GPT-5.5. I went back to see what running it actually looks like now, using Unsloth's quant docs, the model card, AA and the license. Short version: it's stil
Hey r/LocalLLaMA! We're excited to share ORL (On-Policy Residual Learning), our new research on making diffusion language models (dLLMs) significantly faster without sacrificing generation quality. With ORL and our custom inference engine dlmrt, we've achieved: 2,788 tokens/s on a single RTX
TL;DR -- Interpretability might be way more tractable than we thought, and the guy who helped convince everyone otherwise is now saying we can understand models by directly studying neurons and their interactions after all. This essay rewrites fundamental assumptions about how neural networks
Hi r/LocalLLaMA, we're releasing Tyger, a small model that handles full-duplex turn-control for voice agents. What it is Base: NVIDIA Nemotron 3.5 ASR Streaming 0.6B + 14M causal GRU on top. Every 80 ms, with no lookahead, it picks one of three states: - answer: the user finished their turn -
I know I am probably missing the point of this benchmark, but I wanted to see if the model is capable of generating something better or is that the best it can do. So I gave it some encouragement. I find this with development on small models too. You really have to tell it in a little more det
On October 16, 2026, China’s Ministry of Commerce and Ministry of Science and Technology released a draft revision to the Catalog of Technologies Prohibited and Restricted from Export. It proposes adding 40 technologies across AI, biomedicine, and solar PV, of which 23 are AI-related (covering found
There's also a base model. As all OpenMoss releases, they're Apache licensed. Wonder how this compares to Qwen Image 2.1 and Flux Klein 3. submitted by /u/ilintar [link] [comments]
It's clear that today’s SOTA (state-of-the-art) models remain ahead of open-source models. However, if we filter the benchmarks correctly, a different picture emerges compared to what we saw just a few months ago. Today, open-source models are outperforming Sonnet 5, a significant shift, consi
Whenever it comes to Strata and low bit QFN discussion, everyone is talking about Unsloth, ISTA-lab and nobody mentions Agantai with his GYRO series of quants - https://huggingface.co/agentionai/Qwen3.8-Flash-Next-Gyro-GGUF The quants allegedly have simultaniously better KLD, top 1 and lesser
On many tests (math, science, medicine, etc.), they score about 10% higher, use half the tokens, run twice as fast, and cost much less than regular models. mod here, paper link: [2610.18861] Hybrid Reasoning Agents original post on tech_x. EDIT: This method is an adaptation for current word-space re
A couple of weeks ago I read this Wccftech article about Patrick Moorhead's 4 Spark setup. I meant to post this a few days ago but ran some more tests first, and then my workstation had a problem after a kernel and NVIDIA driver update. This post is long enough already, so that will be another post.
Alibaba's Qwen team released a new repository on Wednesday, October 14, 2026. Its goal is to measure how well visual agents can create 3D scenes in Blender based on real-world references. https://github.com/QwenLM/BlenderWorld I think this is a good sign. Companies often build benchmarks in the area
Diffusion language models are the future! submitted by /u/billy_booboo [link] [comments]
Follow-up to u/neuromacmd's post from a few weeks back (https://www.reddit.com/r/LocalLLaMA/comments/1wod07t/). The affinity engine (https://codeberg.org/StillDeadcode/affinity) refuses to start on more than two cards because the author only had two, simulated four ranks on them, and got repea
Going to try these out to see if they have the same looping behaviors that other Bonsai models have had. Still requires their fork of llama.cpp (branch prism) so dont expect it to work with vanilla llama.cpp. Edit: You can use with regular llama.cpp! Will see if there is some way to support th
FLUX 3 Image Klein is a 5.6B open weights model for text-to-image generation and image editing. It takes a prompt and up to 10 reference images and returns one image. Text-to-image, single-reference edits and multi-reference compositions run through the same model, with Qwen3-VL-4B-Instruct as
Hey r/LocalLlama - Today we’re excited to release Muse Spark Open, the most capable US open-weight model to date. Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning. Key Model Specs Parameters: 816B total / 42B active
https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-LiLiCorr-GGUF NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB is a vision-language model (VLM) designed to run everyday agentic tasks locally, using a native 2-bit
New open model to check out ! Doing great on agentic, focused on arabic. From 0.9B to 375B ! Weights : https://huggingface.co/collections/IFM/jais-3 submitted by /u/valcore93 [link] [comments]
Step 5 Preview is StepFun's flagship model for agentic work. It delivers frontier-level performance across software engineering and professional knowledge work, with particular strength in finance. submitted by /u/ResearchCrafty1804 [link] [comments]
Just downloaded the new LFm2.5-24B-A2B LiquidAI model for testing. They claimed some pretty good performance, and I've had good experiences with their prior releases. Some context - I use Ornith 1.5-35B pretty regularly in multiple workflows - sometimes on it's own, and sometimes as part of an AI-Co