Search: “model-releases”

rpc : turn GGML_RPC_DEBUG into a verbosity level and add logs GGML_RPC_DEBUG is now parsed as a number: 0/unset disables debug logs, 1-3 emit increasingly detailed output (events, per-command trace, t

opencl: fix image limit for q4_k dense bin kernels, q4_0 bcast and rms_norm (#30310) opencl: fallback when Q4_K weight images exceed device limits Co-authored-by: Hongqiang Wang wangh@qti.qualcomm.com

opencl: improve fa, allow dk512 for gemma-4, improve dk64 (#30266) opencl: enable Gemma-4 E4B GPU decode Co-authored-by: Hongqiang Wang wangh@qti.qualcomm.com opencl: extend Gemma-4 GPU decode to E2B

Just wanted to share a build I am doing for a client. $18k. Specs: Threadripper 9970x 128gb DDR5 ECC 5600 4x AMD Radeon R9700 AI Pro 32gb(128gb total VRAM) 1600W PSU(GPUs are undervolted and under 210

For the past few weeks I've been trying out converting existing dense models to sparse Mixture-of-Experts models, with no pretraining from scratch. The Idea If you can turn a dense model into an MoE t

It's been 4 years since c.ai first hallucination model, and yet, we're nowhere good enough at LLMs in terms of spontaneity/interesting hallucination features. Fortunately, last year brought new archit

Summary of project status metrics Since StillDeadcode has released his new radiance inference engine, the writing is on the wall for the old vllm-radiance builds, people have moved on to newer and bet

My Jetson Orin–optimized engine, little-gemma V1.0, substantially outperforms llama.cpp. Even after exhausting every practical GGUF option, however, it still falls short of the ideal performance level

I was running Qwen3.8-Flash-Next (base and later Swift-1.5 NVFP4) on a paid pod seat for about a month, and it started answering with short strings that echoed its own earlier reasoning. I assumed the

There is a lot of discussion which quant to use. Especially a lot of post how much speed you gain with FP4, but not much about quality. So i tested some of the models that I use on my R9700. Models: Q

DISCLAIMER: the post and the model card was made with the assist of AI. Hiya, I’m releasing Recursive BitNet N-Gram 102M, a small experiment combining ternary weights, shared transformer layers, and h

Impressive by @river_ai_inc to beat @deepseek_ai rates - cache in particular is tough! Talented team there, full RL + inference stack should be real competition River Inference is live! We're serving

indexes PDFs, Office files, scans, screenshots, audio and video, and finds them by content. A query like 'when did they decide to freeze hiring' opens the recording at that second. * EmbeddingGemma 2

https://preview.redd.it/r2ledkyuntuh1.png?width=1684&format=png&auto=webp&s=9ed4518b2d0f20f44835ebbfac605581da186a57 AesCode generates information-rich visual artifacts such as slides, posters, and da

🧭 New model: Typed Decision, built on EmbeddingGemma 2 Give it a state + any schema of questions → typed, calibrated answers (choice · score · noul). No text generation, no output parsing. 76.4% on ty

No more excuses for GPU-poor folks not to start LLMing! Full 27B-class reasoning in ternary transformer weights, for llama.cpp (CUDA, Metal, CPU) ~9.3x smaller than FP16 (ideal) | 98.2% of FP16 intell

I'm genuinely shocked! I was able to run Qwen3.8-Flash-Next-oQ4e-mtp on M3Max 64GB with oMLX! Even a couple of weeks ago, I wasn't able to get it to run. I just tried the latest commit for fun, and it

Hey r/LocalLLaMA! Maintainer here. Some of you might remember OpenMed from our 1.8 post a few months back. Quick recap: it's an open-source (Apache-2.0) medical AI toolkit with one rule we never break

Alex Heath / Sources: Qualcomm CEO Cristiano Amon says AI companies are “starting to do phones” and asking Qualcomm to support running 100B-parameter local LLMs continuously by 2028 — Cristiano Amon o

I have an app that processes ~500 different documents every day. An agent analyzes them, sorts them, tags them, extracts various legal nuances, creates descriptions, etc. So far I've been using Qwen 3

I love Dash2Dock Lite, but Icedman is always a week or two before updates. I randomly ran pacman for the first time in weeks, not realizing GNOME had a major update. I told it to fix it in DeepSeek Ha

This will be my third update on the bc-250 cluster and for my first forray into local ai I have been having a blast. This has turned from a weekend experiment into something I think I will use in the

I stumbled across this as I was currently having glm5.3 flash run only around 10tok/s basically unusable. With Maya i am running 30 tok/s now. GLM5.3 feels even with this low quant like a much more en

On October 11, 2026 Mina Kimes tweeted that the NFC East had earned zero wins for the week because the division’s only two games were a head‑to‑head matchup that produced no divisional victories, illu

The post is a brief Twitter‑style interaction involving Dr S Maitra and MD Mary Talley Bowden, in which their conversation is described as “an incredible exchange.” A subsequent reply asks how many in

This is a follow-up to my post from yesterday (https://www.reddit.com/r/LocalLLaMA/comments/1x2erdj/qwen3827b_on_a_single_3090_140_toks_on_code_with/) detailing the CUDA megakernel. Thank you all for

What's Changed ollama launch claude no longer shows a warning about Claude connectors by @hoyyeva in #18878 ollama launch codex no longer warns about service tiers by @hoyyeva in #18879 Paused backgro

Alright, I learend a few valuable lessons since I posted about a week ago, and I've made more strides with the DDR4x Ascend 96GB 310P cards I purchased, so here we go, meet the new friendly and less v

Based on my experiments and feedback from claude, it seems extremely unlikely and even if I get it working, not practical because of minimum context. But just asking here as a last effort. I'm able to

We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud

As i use a rather tiny setup 12gb vram gpu and 32bg ram, i was wondering: What setup do you use, which harness? and how do you customize it to run qwen 3.8 flash next swift with a high context length

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

Hi, Because sometimes you need both speed AND quality, I made my own Qwen 3.8 27B Swift 1.5 quant. It's an 8 bits AWQ + GPTQ quant. Made with love and precision (read the model card) on my 4 RTX 3090,

https://preview.redd.it/9k5fw4j47puh1.png?width=545&format=png&auto=webp&s=ff0a6ff6fb69ae9a9bcd579bd612c553fc3e2a00 https://preview.redd.it/xcwzlmo77puh1.png?width=664&format=png&auto=webp&s=c8a637e2e

AI solved open mathematical problems. But the biggest surprise came afterwards. A team at Google DeepMind has used AI to resolve 9 open Erdős problems, including questions that had remained unsolved f

sycl : accelerate MXFP4 MoE with arithmetic decoding and weight reordering (#29809) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54540406 macOS/iOS: macO

opencl: add bin kernels kernel_gemm_moe_q4_k_q8_1_dp4a_bin, kernel_gemm_moe_q6_k_q8_1_dp4a_bin (#30187) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/5457

cmake(s390x): disable z17 target for unsupported compilers (#30297) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54655455 macOS/iOS: macOS Apple Silicon

model : support MiniCPM-V 4.7 (#29416) mtmd : add MiniCPM-V 4.7 support Signed-off-by: tc-mb tianchi_cai@icloud.com model : allow mrope time from an extra position slot Signed-off-by: tc-mb tianchi_ca

server: leave a busy slot untouched when a request pins it (#30295) A request asking for a busy id_slot still ran the prompt cache update on that slot before being deferred. When the RAM cache held a

Banger paper from Meta on AI research agents. (bookmark it) If you build AI-scientist systems, this one is worth your time. The result: A 27B open model beats the strongest open autoresearch baseline

Basalt: Blackwell inference engine Hi all! So over the last week I've been working on a Strata fork that's heavily tuned and can achieve throughput up to 2.6x what Strata usually does on the same weig

I recently started using local LLM for mostly coding tasks for my personal projects. I also have found local models responding much better for topics such as health, fitness, ergonomics etc. compared

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

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

For what it's worth. I'm a mechanical engineer by education and software engineer in practice over the past ~20 years. Playing around with local models has been a recent hobby. Today I decided to do a