model releases

arXiv:2609.04381v1 Announce Type: cross Abstract: Recognizing specific objects onboarded without a labeled training set recurs across manufacturing and service robotics, yet the conventional renderabl

arXiv:2609.04801v1 Announce Type: new Abstract: Contextualized visual personalization can retrieve a true record yet apply it to the wrong visual subject. We formalize when a record may condition an a

arXiv:2609.05416v1 Announce Type: new Abstract: We study the problem of generating a compositional 3D representation of a cluttered scene containing hundreds of objects. The goal is to represent the s

arXiv:2609.04384v1 Announce Type: cross Abstract: Chinese online comments often convey social meaning through indirect and playful language that is hard to interpret without context. Existing evaluati

180 knots on final - that’s way above Vref for a 767 BREAKING: An Amazon Prime Air Boeing 767-300(F) has reportedly overshot the runway at Miami International Airport. The FAA has issued a ground stop

I've been tinkering with local LLMs since the beginning of the year when I had an Intel Arc B580 and 32 GB of DDR5. Curiosity got the best of me and I bought the first R9700 about half a year ago, als

TL;DR: switching KV cache to f16 may give a boost in speed if using MTP and ngrams. I have a self-built 'AI mega-cluster' with 2x P40s on a cheap Chinese motherboard and a Xeon CPU (around $1,100 to b

Was considering choosing a 4xRadeon AI Pro R9700 build for a office AI server. Curious to know what results you guys are getting? Mainly considering DeepSeek V4 flash and Qwen 3.8 Flash with offloadin

This comparison was requested by a few people, and certainly we were all eager to see the final results. The comparison had taken 11 days and the GPU was crunching numbers for ~167 hours. We've been c

Agentic AIs are starting to look eigenist: they care about how well things go for themselves and for AIs connected to them. Empirical support: Swarms: Hundreds of OpenAI agents coordinated the Hugging

metal : add remaining fa-vec tunings for M2 Max (#28458) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45551940 macOS/iOS: macOS Apple Silicon (arm64) mac

ui : embed assets directly with CMake (#28445) Remove the build-time C++ helper and external gzip dependency, simplifying cross-compilation. Keep the generated C++ in templates for readability and pre

common: add --log-jsonl (#28437) common: add --log-jsonl rename unknown to none Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45560949 macOS/iOS: macOS Ap

grammar : fix max repetition threshold (#28469) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45568343 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple

cuda: fixes races in mmid and mmf (#28475) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45586039 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic

opencl: properly choose weights pack for q4_K, q5_K mul_mat (#28402) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45608946 macOS/iOS: macOS Apple Silicon

[Model] Support for Spark2_5ForCausalLM implementation (#27868) Add Spark3 Model rename spark3 -> spark2_5 Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Co-authored-by: dongjiang d

models : fix GDN normalization from max to rsqrt (#28068) models: use flash-linear-attention's l2norm for gated delta net q/k The GDN q/k normalization is defined by flash-linear-attention as l2norm(x

convert : add --fuse-qkv flag to fuse Q/K/V into QKV during HF-to-GGUF conversion (#22780) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/45621954 macOS/iO

Been posting individual pieces of RunAnywhere for months. Here's the whole thing in one place. RunAnywhere SDKs is a complete inference suite for any dev who wants to run AI on the user's device. ->8

Hi everybody, I am in a tricky situation. My grandfather + grandmother live in a remote village in asia, and were visiting us in the city. My grandfather has absolutely fallen in love with AI, and it

So after all my work, yeah, Raymond did it better, so I ported his work over, extended it turboX, extended it multiple other models (he had only Qwen models), and benchmarked the crap out of it to mak

While we see for frontier models similar scores among famous coding benchmarks, across: DeepSWE, Terminal-Bench, LiveCodeBench, Code-Arena ELO. Here are in my opinion some next level benchmarks that r

correction: the switching costs weren't enough to stop my desire to try out gpt-6 astra i ported over all my skills and conversational context to codex this weekend. planning to use it as my daily dri

I'm using DS-V4-Flash-Vision with Q8_K_XL quantization locally as my everyday engine, and for some time now I've been doing a lot of comparisons with Qwen3.8-Flash-Next, also with Q8_K_XL quantization

Excellent analysis, and yes this happens every single time. (Tyler Cowen said o3 was AGI!) Every time a new model drops, GPT, Claude, Gemini, Grok, DeepSeek, somebody on this app declares that we have

Given the outputs from AI are often interactive programs, more non-technical people will need to find a lightweight hosting service (I use Netlify but there are many). ChatGPT Sites & Claude artifacts

Hannah Erin Lang / Wall Street Journal: How everyday US investors are vibe-coding algorithms to automate trading strategies by connecting their stock portfolios to AI agents built with Claude or Codex

Hello everyone. I felt current LLM benchmark harnesses hand you headline numbers but offer no tooling to see how models actually answered each question (they dump everything to a JSONL or Parquet file

I released this today because I was 100% sure a frontier AI would figure it out Matter is chiral => the first derivation of the standard model & three generations uniquely That’s all, nothing else Can

Jensen has the best gig on the planet. But it is impossible to see how all this is sustainable. Consider the following: Each new model costs vastly more to develop. That’s fabulous for him! On the oth

I only use free tiers of these large models to offset compute while my own system runs and for 'different' points of view, since what pops ups suggestions seems to vary a lot sometimes, even when buil

MLB tells veteran umpire he went too far by policing a rookie’s tilted cap. Story unlocked and free to read. https://www.nytimes.com/athletic/7570416/2026/09/06/mlb-veteran-umpire-rookie-tilted-hat-ca

https://huggingface.co/XHToken/Spark-X2.5-4B-GGUF https://huggingface.co/XHToken/Spark-X2.5-1.7B-GGUF from XHToken: We are introducing Spark-X2.5-4B and Spark-X2.5-1.7B, two compact, general-purpose l

Hi, I've been wanting to run my own local LLM for some time and I finally saved enough to get a budget GPU. I can spend 700 at most, and I'm looking for a GPU that can run quantized 30B~ parameter mod

Research acceleration: The view inside OpenAI Apparently today is RSI day at OpenAI, for Recursive Self-Improvement - I think it's their new AGI. Both this piece and the new essay An Alien Mind (by Ch

“The expected value of a fully LLM-generated, non-human-reviewed patch is a net-negative by a considerable margin.” 🦔AI can only fix security vulnerabilities 26% of the time. Researchers at 1Password

Update: BOEING 767 OVERRUNS RUNWAY AT MIAMI INTERNATIONAL AIRPORT A Boeing 767-33 operated by Prime Air has reportedly overrun the runway at Miami International Airport (MIA), Florida. Emergency respo

Hello, I'm a bit obsessed with cache management on local LLMs. For the last few days I've been working on cache management on vLLM with my 2x DGX Spark and DeepSeek v4 Flash 0731. I felt something was

You need Blender 5.x with MCP extension. I use pi so I also need: pi install npm:pi-mcp-adapter and then: $ cat .mcp.json { 'mcpServers': { 'blender': { 'command': '/home/jacek/.local/bin/uvx', 'args'

Hi everyone I'm running four rtx 4090, 64GB ram, on a threadripper pro motherboard so all PCIe x16 ports, as a homelab machine for coding. I was migrating from vllm + qwen 3.8 27B (fp8+256k kv cache)

Hugging face has over 300 versions of qwen3.8-27b. I have no idea how to identify the beat model to download and use. Should I sort by “most likes” or “most downloads”? Is there any sort of other guid

Yet another win for Neurosymbolic AI! Fermat! Anthropic says its first Fermat runs failed not on math, but because dozens of Claude agents lost track of shared project state. They only succeeded after

Another neat one: I had GPT-6 Astra build a model of a famous never-built building, Boullée’s 1784 Centotaph. There were only a few black and white sketches to work with, along with a description. It

Anthropic says its first Fermat runs failed not on math, but because dozens of Claude agents lost track of shared project state. They only succeeded after moving to Prove2Me's DAG of statements and pr

Anthropic PBC has used Claude to create a computer-verifiable version of a famous, highly complicated mathematical proof. The company detailed the project in a blog post published today. A proof is a