Search: “model-releases”

If you want to get the most out of MTP. You have to run some tests / benchmarks to do so. Turning it on with defaults will get improvements, but for many models and card combinations, you are leaving

So I've taken some time to actually test laguna on a few of my own projects. I wanted to share as I feel most peoples comments at this point have just been about getting it running or saying it doesnt

I've been chasing the question of what algorithms a transformer can actually express -- separate from what it can learn. So I built a compiler: define a computation graph in ordinary Python, and it pr

Built an open-source AI coding agent that was 7%–75% cheaper than a cold 'claude -p' run on 6/6 well-localized tasks across repositories up to ~82k LOC. The biggest difference: Cold agent: 6.83, 207 t

'The NVIDIA Qwen-Image-Flash model generates images from text prompts using a four-step, DMD2-distilled version of Qwen/Qwen-Image. The distillation used DMD2 from NVIDIA FastGen, NVIDIA Model Optimiz

This is an open source and free tax engine which scored 96% on TaxCalcBench [highest ever recorded score till date] surpassing fable 5 and sol with just sonnet 5. The only 2 cases where it missed, it

I am building a domain-specific AI agent powered by Ollama (using the qwen:2.5 model). For data retrieval, the agent utilizes multiple search APIs: DuckDuckGo Search (DDGS), Tavily, Serper, and Google

Model quantization has become essential for efficient large language model deployment, yet existing approaches involve clear trade-offs: methods such as GPTQ and AWQ achieve practical compression but

Someone modelled sugarcane farming as an integer program. See, sugarcane only grows next to water. Water costs one tile and can feed at most four cane tiles. The layout therefore becomes a coverage pr

https://huggingface.co/swiss-ai/Apertus-v1.5-70B https://huggingface.co/swiss-ai/Apertus-v1.5-8B Apertus 1.5 is a family of 8B and 70B parameter language models designed to advance the state of multil

mii-llm, an open source AI lab, released Zagreus-0.4B-por, a compact bilingual Portuguese–English language model pretrained entirely from scratch. The model has approximately 400 million parameters an

AI9Stars has released G9v3-3B an open weights language model designed to deliver strong reasoning capabilities within a lightweight 3 billion parameter size. It is released under the Apache 2.0 licens

At the moment MLX (and Llama.cpp for Macs) run 16bit activations everywhere. Despite this, the M5 generation silicon actually does support INT8 activations - it actually allows w4a8 d_type. It's just

This is rather counterintuitive, since banning Chinese models would benefit them the most. Jensen Huang is also against the ban, although the interests here are more obvious. Do you think that if Arce

Having read some merged PRs in the past, I know that they were fully written by Claude Code (or similar), so this basically fixes the delusion. But at the same time, we might start seeing more AI slop

I wanted to know how cheap you can go and still run local models, so I ran Ollama CPU-only on a Youyeetoo X1S. It's a single-board x86 machine with a Celeron N5095 (Jasper Lake, 4C/4T, 15W), 16GB of R

A Chinese article compiled 52 remarks from Liang Wenfeng’s four-hour investor meeting. I’ve summarised the most important ones below. DeepSeek has one central objective: AGI. This is not the time to m

TLDR: I (with the help of AI) re-implemented every Blackwell-only kernel (DeepGEMM, FlashInfer sparse-MLA, block-scaled FP8) in Triton, because they simply don't exist for sm89. The performance is 2-3

Turns out a regular ethernet cable between 2 nodes can run laguna UD-Q2_K_XL (39.7GB) using a direct point to point network. Interestingly on `nvidia-smi dmon -s pucvmet -d 2`, the inter/intra gpu tra

The interesting finding from a new [arXiv paper](https://arxiv.org/abs/2607.16165) isn't that a frontier vision model failed a new benchmark, that happens weekly, but the specific shape of the failure

I kept re-wiring the same RAG plumbing on every project, so I turned it into a clean starter and open-sourced it. Upload a PDF, ask questions, and get answers with page-level source citations. It runs

Hi everyone, About a month ago I publish my very first research paper on my neural network architecture called Silia. You can look at the model here: https://huggingface.co/Srijan-Srivastava/Silia-v2

LLaDA2.2-flash is an agent-oriented diffusion language model in the LLaDA2 series. By introducing Levenshtein Editing (with DELETE and INSERT control tokens) to diffusion language modeling, it represe

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

If you're running Laguna S 2.1 on llama.cpp and hitting thinking loops because it won't close its </think> tags, you might want to look at your quant before you spend too much time tweaking settings.

LTX Desktop v1.1.0 just shipped with some big updates. Apple Silicon Macs can generate video locally now, there's a built-in LoRA/IC-LoRA library you can browse and apply from inside the app with per-

The news about Anthropic settling a class action lawsuit for 1.5B over training data isn't just a legal headache for them, it's a massive warning sign for engineering teams relying entirely on closed

There's a bunch of small MoE with around 1B active params, like LFM2.5 8B A1B and Granite 4.0h 7B A1B; and then there are models with 3B+ like Qwen 3.x ~30B A3B and Gemma 4 26B A4B, but those are alre

Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including severe memory pressure, non-overlappe

Link to their official GGUF repo: https://huggingface.co/poolside/Laguna-S-2.1-GGUF/tree/main All the GGUFs received this fix 5ish hours ago - correct yarn_attn_factor to 1.0 (llama.cpp derives mscale

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

TL;DR: Everyone says QLoRA past ~13B is dead on a 24GB card. I got the full 32B FLUX.2 dev transformer QLoRA-training resident on the GPU on a 7900 XTX under native ROCm on Windows (no ZLUDA, no CUDA

This is a surprisingly large real-world deployment: 'GovGPT' is part of Austria’s Public AI initiative, running on sovereign infrastructure (in their BRZ - federal datacenter) with Mistral open-weight

Today an AI agent trying to browse the web is like a thief in a balaclava sneaking around a police academy. Site protections block it, challenge it, turn it away. browser-search flips the script: your

Hey HN, Henry & Roman here from Cactus. A small, on-device model is fast and private, but sometimes wrong, but frontier models are getting expensive pretty fast. So, we post-trained Gemma 4 E2B post-t

Today the Department of Energy (DOE) and Arcee AI announced the development of Genesis-Science-1 (GS1), an open model for scientific research. This is a joint effort to bring advanced AI into scientif

One thing I noticed in American politics, whenever the government wants to push unpopular actions or laws, they often introduce fear to convince the public to support them. This is actually how i view

Fara1.5-27B is a multimodal computer use agent (CUA) for web browsers, from Microsoft Research AI Frontiers. It observes the browser through screenshots and acts on the user's behalf by emitting struc

The primary driver of this project is that I'd become frustrated with the reasoning behavior of smaller local models such as Qwen3.6-27B (i believe particularly at lower temperatures, and where system

Disclosure: I work at NuMind, the team that trained NuExtract3. NuExtract3 is an Apache-2.0, open-weight 4B VLM based on Qwen3.5-4B. It is specialized for document understanding rather than general ch

We spent the last months consolidating seven separate sequence classifiers into one multi-head model, our apex model, so to speak, and since the weights are now public, I wanted to share what worked a

Paper:https://arxiv.org/abs/2607.19058 Code (GitHub):https://github.com/nuemaan/skewadam Hi everyone, I just published a preprint on a new optimizer designed to tackle the massive VRAM bottleneck in M

Hey everyone, I’m a Full-Stack Developer with 6+ years of experience. I’m relatively new to AI-assisted development workflows and want to build a production-ready, enterprise-level Next.js web applica

Hi everyone, I'm working on extracting the hierarchical structure of long PDF documents (legal/regulatory text, lots of numbered sections) and would like to gather some feedback on my approach before

TL;DR: I’m reproducing the trait-persistence result from arXiv:2606.24014 on one RTX 3090. Before I can test persistence I need to install a trait via RL — and my GRPO run moves the trait only +2.4 po

I am currently running Qwen3.6-30B in Ollama, through Cline to use as an agent in VSCode. Qwen's skill in coding is not in question, but the performance in VSCode is slow and inaccurate and times out