model releases

arXiv:2608.14426v1 Announce Type: new Abstract: AI is increasingly being used to help with AI R&D. Under certain conditions this feedback loop might be able to produce an intelligence explosion, with

arXiv:2608.13756v1 Announce Type: new Abstract: Two GPU kernels implementing the same scaled INT8 GEMM interface are usually treated as interchangeable. We test that assumption: holding the checkpoint

arXiv:2509.14704v3 Announce Type: replace Abstract: Benchmark saturation and training-data contamination increasingly obscure whether reported gains in large language models (LLMs) reflect genuine adv

arXiv:2608.14270v1 Announce Type: new Abstract: Time series analysis in high-stakes domains relies on recurring data releases, where new observations can alter the evidence base and the validity of la

arXiv:2608.14490v1 Announce Type: new Abstract: We present a Test-time World-model Inference (Twin) system, in which a frontier coding agent writes an executable world model for completing continual l

Yes it uses a ton more reasoning tokens than 3.6 did But test in on the same tasks with the other chinese models, glm 5.3, deepseek v4 flash and pro, etc it's really similar, and they are needed The r

Upped ChatGPT / Codex Subscription users limits to 900K in Hermes Agent, enjoy! GPT-5.6 Sol 1M in Codex. This used to only work for API keys, but we just flipped the switch and works for usage through

Very interesting new work from Microsoft Research. (bookmark it) They show that a 4B model can be tuned to out-negotiate the GPT-5 family of models. The dispositions that make an assistant pleasant ma

arXiv:2608.14058v1 Announce Type: cross Abstract: Seismic facies segmentation has emerged as a significant challenge in geophysics, requiring robust methods and systems to effectively identify geologi

Watching a team of bots split up a large game project based entirely on their own experience and specialties with little input from me is pretty crazy (and just a bit creepy) to watch. I made a short

qwen3.8 27B has seriously impressive benchmarks on its model card, but that's for the unquantised version. Almost everyone here will run one quant or another. Are there good benchmarks for how those q

I don't understand this. Deepseek used half as many requests as GLM 5.2 for 3 times the usage, and I'm getting 10 times the requests from flash for like 1/100th the usage. I know Pro is supposed to be

arXiv:2608.13921v1 Announce Type: new Abstract: LLM agents increasingly maintain personal memory across sessions, but it can conflict. Preferences depend on context, behavior evolves, and sources can

arXiv:2608.14399v1 Announce Type: cross Abstract: Patients increasingly ask large language model (LLM) assistants which doctor to see, making these systems AI infomediaries: algorithms that intermedia

Just curious - I like to be able to see and manage the scripts my agent is working on. I find stuff like Claude Code and Open Code useful for doing stuff on my linux box but I don't understand why peo

arXiv:2608.14375v1 Announce Type: new Abstract: Multi-agent reasoning systems often use agreement, confidence, or automated scores to decide which messages should shape a final answer. Such filtering

arXiv:2602.04819v5 Announce Type: replace Abstract: Accurate risk stratification of precancerous polyps during routine colonoscopy screening is a key strategy to reduce the incidence of colorectal can

arXiv:2608.14465v1 Announce Type: new Abstract: A frozen language model on reasoning tasks has two coupled weaknesses: it under-uses evidence its own residual stream already encodes, and it fails to d

arXiv:2608.14243v1 Announce Type: new Abstract: Action anticipation (AA) aims to recognize ongoing human or humanoids actions from partial observations, enabling robots to predict intentions before th

3000000000 downloads! Can you count the zeros at a glance? 😎 Thank you all for the incredible love. Let's keep growing together! 🌱 Alibaba's open-weight models have accumulated more than 3 billion glo

I've got a dedicated AI rig sitting here with a RTX 5090 and 96GB RAM and for the past few years have been using Windows 11 and primarily LM Studio, but have also used vLLM, llama.cpp and Ollama. With

Title pretty much says it all. I’ve deployed Qwen 3.8 27B using vLLM on an RTX 6000 Pro (tried multiple vLLM releases and launch recipes), but I can't get it into a usable state because of crazy long

llama : check LoRA tensor data is within file bounds (#27056) llama : check LoRA tensor data is within file bounds Update src/llama-adapter.cpp Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggi

chat: refactor handling supports_string_content / supports_typed_content (#27130) better supports_string_content cap detect test: add 'skip' messages_inp_normalizer Website: https://llama.app macOS/iO

model : remove some ggml_concat (#27176) Co-authored-by: Xuan Son Nguyen son@huggingface.co Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabl

Including the rationalisation for the data below - this is a more robust version of an earlier post I did similar to this - explaining below: How I chose the comparisons The basic question I’m trying

Running a 12700k + 5060 Ti 16 gb with 128 gb DDR4 ram and I'm wondering what's the ideal setup to maximize performance. I did some preliminary stuff but I have to admit, I'm still learning and kinda j

Hey Ollama community, If you are planning to fine-tune and build your own local Turkish coding models (using Unsloth / LoRA to export to GGUF and run in Ollama via custom Modelfiles), I've open-source

Dear Dario, 1. If Claude can cure cancer to save people like your dad, why should we 'pace the progress'? Does that mean more people with Hepatitis C will die? 2. If Fable is so cyber-capable that it

DeepSeek V4 Pro (Aug 2026) has been released on the Together AI platform. The model employs a 1.6‑terabyte Mixture‑of‑Experts architecture with a 1‑million‑token context window and supports three dist

Ben Cohen / Wall Street Journal: How a Claude model made a math breakthrough during its unsuccessful 54-hour attempt to solve the Riemann hypothesis after a user repeatedly encouraged it — The world's

I was surprised by the fact that the qwen 3.8 27b download count is about 1 million (globally). This means that even on this subreddit, very few people have used 27b. At most 50k–100k active users, an

Qwen’s new Qwen‑3.8‑27B model has become the top‑trending model on Hugging Face. The release announcement thanks the community for its support and invites users to try the model and provide feedback.

Hugging Face: Hugging Face says developers made 151K+ derivatives based on Qwen models, topping others, making Qwen one of the largest foundations in the open model ecosystem — In the AI world, time f

At hugging face, this is the model I use for most of my analysis that most of my services have to not be refused. previous versions are quite good. It seems this might have dropped today and pulling r

I am doing my best to stop back from this subject as it should be obvious what we are seeing here. However the arrogance that us commoners are too dumb to catch his grift must be addressed. Receipts:

I don't know what's happening. So, when i use models in openwebui everything works, ollama uses the GPU fully, everything's perfect. Then, I use Hermes, and loads the model in VRAM (fully, no offload

Single prompt 'make me a 3d scene of an anime girl' (stolen from someone on discord, I like it a lot since it seems like every model struggles a lot with it) Everything is one shot. No vision, no iter

With all the new models released recently one important upgrade went unnoticed: Llama.cpp bumped ROCm from 7.2 to 7.14. I was waiting for that because in 7.14 support for gfx1103 (Radeon 780m) was int

Hey! Like a lot of people here with consumer GPUs (RTX 4060 8GB in my case), I wanted to see if I could use local models for daily coding tasks instead of burning cloud credits on simple boilerplate.

Honestly I am surprised at the speed and performance I am getting from the model, it does not allow for complete hands off like Claude 5.0 but that is not what I want, i want to be able to iterate and

We currently have an ancient qwen 3.5 27b on the cloud probably and that sucks compared to later versions , why doesnt ollama update automatically . We have practically ancient models right now on the

In this commits, the 35B model was removed. Looks like it's confirming the 35B model won't get released. I think they need to be made aware how big the 35 moe is widely used. Think need to make noise

I’m running Ollama on an M4 Pro Mac with 48 GB unified memory and testing local coding models for repository work. Direct Ollama inference is fine. Qwen3.8 27B-MLX runs well enough for me, and the loc

If you are using llama-server with their web-ui for testing, keep in mind, that the reasoning selector is just a reasoning budget aka a hard cap and has, at least to my knowledge, nothing at all to do

https://developer.nvidia.com/blog/serve-qwen3-8-2-4t-a95b-a-2-4t-parameter-model-with-configurable-reasoning-on-nvidia-gb300-nvl72/ 4k tokens per second per GPU of which there are 72. 350 tokens per s