Search: “models”

A Reddit post from the r/ollama community documents a user's experiment running Google's Gemma 4 model locally via Ollama with web search (internet access) enabled, which resulted in the model becomin

webAI released TwIL LM3 Pro on September 30. I haven't seen it posted here yet, so I went through the model card, and their comparison chart is attached. It's a 3.66B model built on IBM's Granite 4.2

Around 3 weeks ago, I posted on this subreddit about how Jev used my one-year-old architecture, og post: https://www.reddit.com/r/LocalLLaMA/s/VpuMJt577S Then, just after that, I introduced Laya, the

Speculative decoding accelerates autoregressive generation in large language models. In each drafting stage, a lightweight draft model proposes tokens that the target model subsequently verifies. With

Hey everyone, I'm looking for a small uncensored model to run locally with Ollama. Nothing fancy. I just want something I can ask everyday questions without it refusing or lecturing me every other mes

Meet Bev. She is a decision model (the Jev / Nimble kind: you give her a situation and a question, she gives a probability for each answer), fine-tuned on Qwen3.5-9B to pick the worst answer on purpos

Hey everyone, I’ve been working on a game called Anyworld. It’s a browser-based multiplayer (single player also supported) text adventure inspired by the early days of AI Dungeon, especially its brows

Hey guys, Last time I tested Qwen3.8-Flash-Next on its own. This time I put three Qwen3.8 checkpoints through the same 10 tests on the same RTX PRO 6000: RadixArk/Qwen3.8-27B-NVFP4 (dense) orcarouter/

I've been comparing and working on Gemma 4, Phi-4-Mini, and Qwen3-4B for local LLM use on an 8 GB Raspberry Pi 5. The results were indeed close, but each model has a different strength: Gemma 4 E2B: a

Recently, the new DeepSeek-V4.1-Flash architecture showed how a causal encoder-decoder can work, but it was trained from scratch. Model Grafting does it to an existing model: cut at some depth, let th

Quote: DeepSeek is training a 2T-parameter model and plans to eventually build an 8T-parameter model. https://x.com/wallstengine/status/2101982843656388644 Current DeepSeek models: Flash parameter cou

Sorry for the pretentious name, I know, I know.. It just contains all the pieces I would like to see a AGI model to have, and I can't stand the temptation. Before throwing rocks at me, please take a g

I made this because I was getting genuinely annoyed at trying to have a normal conversation with LLMs. Even with prompting and various tricks, most models I've tried still have this 'AI assistant' vib

Original Source from DeepSeek WeChat Official Account: https://mp.weixin.qq.com/s/qg0NU3NNUbp1co2PdkAPAg Today we're officially releasing the DeepSeek V4.1 Flash model. It is the smallest model in our

Up front: I'm one of the people building the page-perception layer used here. We started by testing small local models. The result turned out to be more interesting than the original test. 12 small mo

I’ve been thinking about this after using more agentic/local coding models. A lot of the newer models are surprisingly good at continuing on their own. But sometimes that seems like the problem. If a

I ran a side-by-side ML text-processing and model-training workflow using Fable 5.1 vs. Astra (both on xhigh), and the results could not have been more different. Warning, long post. TL;DR -- Astra co

Not even sure if I'm allowed to post this, what with the 'completely/primarily LLM generated copy' rule (the post itself is fine, but the repo/model I'm sharing definitely is, whoops) and the whole li

Has anyone figured out how to enable speculative decoding with deepseek v4 flash 0731 on llamacpp? I’m on the right release for llamacpp (b10228 or earlier) and running am17an’s draft model with unslo

Mage-VL is a codec-native, proactive-streaming multimodal foundation model for image and video understanding, whose visual encoder is trained entirely from scratch at a compact 4B scale. It targets a

This r/StableDiffusion Reddit thread discusses community recommendations for photorealistic image generation models that can run within a 16GB VRAM constraint, a common hardware limit for consumer GPU

A Reddit post on r/StableDiffusion announces the anticipated release of an ERNIE image **editing** model from Baidu, complementing the already-available ERNIE-Image-8b generation model from Baidu, whi

New version of my MiniMax H3 timeline workflow released Some very important bug fixes included, and a lot of improvements. The YouTube video above includes a lot of tips for using the workflow in addi

hello, I currently use swift qwen3.8 gsq rco in iq3 xxs in strata. The model is only used for hermes agent. I have 64GB of ram + 32GB R9700 where the model runs on. But I also have an rx7800xt with 16

This is related to my previous post where I shared an encoder-only transformer model trained on ohiot1dm + shanghait1dm + azt1d datasets. This time I trained the model on the outputs of my T1DM patien

So PewDiePie decides to fine-tune a local AI model called Ajax on his own computer. Pretty normal stuff for local model fans. To make his dataset, he uses OpenAI's API. OpenAI catches him using their

We did a study: does post training actually make LLMs funnier? We used open models that publish every stage of post training, so we could compare a base model with the future models it became: Tulu 3

TL;DR -- You should probably just use base Qwen3.6-35B, as only Occamy-1.0 is competitive with it. Tiel is a major let-down, worse than Ornith. KAT surprises (good), Nex surprises (bad). This post is

I've been building a small decision model for agent loops: gates, routers, 'should I ask the user or just act' checks. It's out now as Mica v0.1 4B (Apache-2.0). What it does You give it a state, a qu

Model Overview Ling-3.0-flash-VL inherits the language, reasoning, and long-context capabilities of Ling-3.0-flash, while extending them with native image and video understanding. The model has 124B t

Context: we build an open-source (MIT) self-hosted database client and added a natural-language-to-SQL assistant that can point at a local runtime like Ollama instead of a hosted API. I want to share

Laya is an open-weight (Apache 2.0) 'System 1' decision model from Convai Innovations, built by Nandakishor M as an open alternative to TypeSafe's closed Jev API. Instead of generating text, it takes

This weekend, I did a fun experiment to create something similar to Jev. I LoRA fine-tuned Qwen3.5 4B using a mix of publicly available datasets and synthetic data. For the synthetic data, I used Deep

Three weeks back , i posted SHADOW-250M here. It got 360 upvotes, 293 on r/LocalLLaMA and 94 GitHub stars. Thank you. That model was 60 MB, ran around 400 tok/s on CPU and could retrieve records from

Being a person obsessed with testing new models that come out, times are really insane for me. Tested different kinds of TTS and voice cloning models but none of them gets it right in terms of emotion

Ling-3.0-flash-Fin is the first finance-enhanced model in the Ant Ling family. Developed by Ant Group with leading financial institutions and domain experts, it extends Ling 3.0 flash through continue

## Qwen3.8-Flash-Next-NVFP4 (inferact) vs Qwen3.8-27B-FP8 (qwen) Slammed with work and no time to pretty this up. Qwen wrote most of this but I checked the data. All tests done on the same rig, same p

A hallucinated event, Crono awakens in his modest bedroom of 2095... I am using local models since 2025 January. My daily driver is qwen 3.6 35B A3B, which works pretty well for coding tasks, but I al

TL;DR: Every public low-bit GGUF of this model is secretly ~4.70 bpw. Shim the rows to 256 and it becomes a real 3.07 bpw / 11.77 GiB file that runs 262K context on 16GB. Needs patched llama.cpp — not

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 have been searching for suitable model to run on my 8GB RAM toy, NVIDIA Orin Nano Super 8GB. This little toy was priced at 249 earlier this year (not any more), and pulls very little power when idle

If you scroll down from the countdown at https://huggingface.co/Qwen/Qwen3.8-27B, you see a big model card with a bunch of sections: Highlights, Model Overview, Quickstart, Best Practices, Citation, e

https://huggingface.co/Motif-Technologies/Motif-3-NVFP4 On benchmarks, Motif 3 scores very, very close to DeepSeek V4 Flash 0731 in English vs. DeepSeek V4 Flash 0731 in English in various benchmarks,

This PR should be ready for testing now. I tested with a very small (8B params) sub-model extracted from the original one. Appreciate if someone can test with the bigger model. GGUF(for testing) from

https://huggingface.co/tsfrm/vacuum-16t A 16.5-trillion-parameter model that contains nothing. This model is just a ████ you to the labs and companies who say that 'haha I have the biggest model out t

Hey everyone, ​I recently finished pre-training BetterGPT-150M, a small, lightweight causal language model with ~152 million parameters.Trained on 15B tokens. Dataset & Training: Trained across stable

This r/ollama post discusses a tool for easily linking models between LM Studio and Ollama without duplicating disk storage. Both Ollama and LM Studio are popular local LLM tools, but they store their