Search: “models”

Just came across this coding benchmark: SciCode Artificialanalysis.ai reports a ranking which contradicts the feeling we've towards those models in real life coding. Is Gemma 4 really that good, or a

Just wanted to share my agentic coding benchmark run of DSv4F 0731 at both High and Low reasoning efforts (not Max)... I ran a 109-question subset of Aider Polyglot (the JS/C++/Python languages), base

It is one of the best local models ever released, in both 20B and 120B versions. I always come back to it, especially the 120B version. Its only competition is, in my opinion, Qwen 3.5 122B, but that

AI9Stars has released G9v3-39A5B an open weights language model designed to deliver even stronger reasoning capabilities than ai9stars/G9v3-3B with its 39B and 5 active experts. It is released under t

https://preview.redd.it/3zcvpbds14hh1.png?width=1911&format=png&auto=webp&s=a79aafb71eeca97638da93d2591902631e897fd5 I tried a test similar to the recent model-quant comparisons, but this time I focus

Sorry if this is asked a lot, but I was wondering if there is any clear winner on the Quantization versus Model Size debate? I can run Qwen3.6 27b at Q8, Laguna at Q6, and the new Deepseek Flash at Q3

Every time a model drops from a Chinese lab the thread fills with people who already know who made it, and the guess is usually Alibaba. There was a thread here recently asking what separates the open

I've been thinking about building a pipeline to generate reasoning training data for LLMs, but I want to avoid the common failure mode of synthetic data where you just generate the same template with

Context: I want to give the community an Open Research (well open under Apache 2.0 clause) - tool that allows everyday users like us to look deeper into the local models we use consistently. Mechanist

Most quantization works like this: pick a bit depth, apply it everywhere, maybe let imatrix take a rough guess at what matters, ship it. Most don't check which specific weight groups can take a hit an

Recently I bought an Ollama Cloud sub and accidently spent my whole 5h quota upon using DeepSeek V4 Pro... but why? isnt it supposed to be a cheap model? Youd think there would be a correlation betwee

from kwaipilot: Following the release of KAT-Coder-V2.5 in July, we are pleased to release the open-weight version KAT-Coder-V2.5-Dev, an MOE model with a total parameter count of 35B and 3B activated

Shoutout to this awesome guy - https://www.reddit.com/r/LLM/s/IDUyU3v9ap Thanks to his project, BigMoeOnEdge https://github.com/Helldez/BigMoeOnEdge, I managed to successfully run a 35B MoE model on j

This post discusses running Google's Gemma 4 QAT (Quantized Aware Training) 12B model on a GPU with 8GB of memory while maintaining a 16k token context window. The author likely shares performance ben

Mistral-7B v0.3 model achieves significant memory optimization when running at 128K context length in llama.cpp, reducing live VRAM usage from 22,657 MiB to 13,235 MiB while maintaining minimal perfor

This Reddit post discusses a common ComfyUI issue where users cannot locate spatial upscaler models for img2vid workflows. The problem typically stems from placing spatial upscaler models in the wrong

Stability AI announced the launch of Stable Audio 3, a family of three AI music models and one audio-based special effects model. Most of these releases are 'open weight' models trained on licensed tr

Ring-2.6-1T is a trillion-parameter flagship reasoning model designed for real-world complex task scenarios, now available as an open-source model. The model features about 63B activated parameters pe

LTX-2.3 is an open-source video generation model released in January 2026 that supports LoRA fine-tuning for customizing styles, characters, and use cases. The Reddit post compiles available LTX-2.3 m

Kimi K2.6 is an open-source model featuring advanced coding, long-horizon execution, and agent swarm capabilities that is now available via Ollama Cloud . The model excels in coding and agentic tools

A user reported satisfaction with Gemma 4 Cloud but switched to GLM 5.1 due to API errors, noting that the alternative model consumes significantly more resources. The post likely discusses the perfor

Ernie Image Turbo is a text-to-image generation model that can run efficiently on consumer-grade hardware like RTX 30 series GPUs with limited VRAM by using INT8 quantization. The post discusses techn

This r/ollama thread addresses a known compatibility issue where importing multimodal GGUF models into Ollama using a separate mmproj (multimodal projector) file fails to enable vision capabilities. O

This r/ollama post addresses a commonly reported behavior where Ollama's GPU usage remains at or near 100% even after a model has finished generating a response. Certain models appear to 'hang' after

This r/StableDiffusion Reddit thread likely discusses the topic of hand generation quality when using ZIB and ZIT — two AI image generation models from the Z-Image ecosystem used in Stable Diffusion a

ERNIE Image is an open-source text-to-image generation model developed by Baidu, built on a single-stream Diffusion Transformer (DiT) paired with a lightweight Prompt Enhancer that expands brief user

A Reddit user on r/ollama conducted a hands-on benchmark comparing Gemma4:e4b (Google's compact ~4.5B effective-parameter edge model) against Gemma3:27B, GPT-4o-mini, and Gemini 2.5 Flash, all run or

This r/ollama post describes a streamlined method for performance-testing locally-running large language models using the Ollama framework, achievable with just three terminal commands. It likely intr

A developer shared on r/ollama how they built a custom VS Code extension that routes Claude API requests through locally-run models via Ollama, dramatically reducing cloud API costs to approximately $

A Reddit thread in r/ollama where a user reports experiencing AI hallucination issues when running local language models through Ollama. The discussion likely covers symptoms such as models generating

I was unable to retrieve the specific Reddit thread content from that URL through my search. Reddit threads often require direct access to load user-generated content, and the search did not return...

Users running OpenClaw with `gemma4:26b` via Ollama encounter significantly slow or timed-out first turns in a session, even though the model responds quickly when queried directly through raw Olla...

Users in the Ollama/Open WebUI community commonly report being unable to query PDF documents via the Open WebUI interface when using a locally hosted Ollama backend, with the model failing to recog...

The ASUS ROG Flow Z13 (2025) with AMD Ryzen AI Max+ 395 (Strix Halo) and 128GB of unified LPDDR5X memory is a capable portable option for running large LLMs locally, with ASUS officially stating it...

LTX-2.3 is a DiT-based audio-video foundation model from Lightricks that generates synchronized video and audio within a single model pass, representing a significant upgrade over LTX-2 with improv...

The Mac Mini M4 Pro with 48GB unified memory is a popular choice in the local AI community for running large language models via Ollama, as its Apple Silicon architecture makes all 48GB of RAM dire...

This tutorial demonstrates how to use mitmproxy to inspect the actual HTTP traffic sent from a Quarkus application to a local Ollama model via its OpenAI-compatible endpoint, revealing the real JSO...

A Reddit post in r/ollama describes a user's experience attempting to run LLMs locally via Ollama to avoid cloud API costs, only to encounter severely degraded performance — waiting 13 minutes for ...

Having a ‘Killer Application’ that everyone wants to use helps sell hardware, plain and simple. DeepSeek V4 Flash 0731 isn’t an app of course, but I think it’s going to be the major catalyst for getti

Looks like the Ling team open weighted a much smaller version of the Ling-3.0-flash they open weighted a few days ago. It's 8B params with 1.3B active, and seems to fall between the 4B and 8-12B Qwen

Hey everyone, I've been experimenting with the new DeepSeek-V4-Flash-0731 release locally using the Unsloth Studio Q8_K_XL GGUF with OpenCode. Overall, it's been working really well, but I've noticed

Disclaimer - no LLM was used to write this post/note As larger post about my setup will come later, want to give heads-up to folks who use VLLM and >= 2 GPUs. So I have pretty meaty server (8 channel

I've been tuning my new Radeon AI Pro R9700, and figured that this would be useful information for people who are trying to optimise their setups. I'm pretty happy with these results and looking forwa

I'm the author, so discount the enthusiasm accordingly. This is an unaffiliated community port, not endorsed by the vLLM project, which it uses to verify its correctness. What started it: I love vLLM,

A follow up to the launch of Mference, it now supports and runs Inkling-Small 276B-A12B. Inkling-Small (Thinking Machines, Apache 2.0), from the pipenetwork/Inkling-Small-MLX-4bit conversion: 276B tot

TensorSharp's MoE CPU-offload feature has been merged into main. Here is the parameters description of this feature: Mixture-of-Experts CPU offload: --n-cpu-moe <N> | -ncmoe <N> Keep the routed MoE ex