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So everyone has been yelling about how I should be using Gufo instead of halogen because it's open source and it's "just as good or better". Checking in on their GitHub (GitHub.com/gufo-org/gufo) got me immediately .. "Qwen 27B Q4: 70.56 tok/s single user, 123 tok/s with 8 users" on a strix halo dev
Hello guys. Recently, there has been a boom in game decomps and recomps thanks to AI. If you look at the r/decomps and r/recomps subreddits, you can see it. They mostly seem to be using Claude or Codex.I wonder if it would be possible to do something similar with a local AI model. Could Qwen 3.8 27B
Hello guys! I have been experimenting with qwen 3.8 for a long time and I hadn't been able to get reasonable speed. I am on a 5060Ti 16 GB, and although this gpu can game, I am aware that AI demands more than 16 GB. I am on a Fedora 44, AMD Ryzen 9600x and 16 GB system ram (16 GB system ram and 16 G
Hybrid search, reranking, query decomposition, and query expansion are often treated as must-haves for good RAG. We wanted to see how much each actually helped, so we tested them. Same model, same embeddings, same documents, across all 824 multi-hop questions in FRAMES. We built 18 pipeline variants
A few days ago I released Jeff-Qwen3.5-0.8B, a small "System 1" model that picks between options you define and returns a calibrated probability for each, in one forward pass. Speed was great on my M4 Max and RTX PRO 6000, but as a general zero-shot classifier it trailed the big models. Then it occu
40 year tech gap? No problem! The Tandy runs DeskMind, a native DOS program. It talks over WiFi (a PicoMEM 2 card with mTCP) to a small Python server on my PC. That server drives Qwen3.8-27B (NInfer on a 5090) and Krea 2 (ComfyUI on a 4090). The 286 never sees JSON, base64 or a PNG. It gets pl
now you can use MTP with Qwen Flash Next, time to switch from Qwen 3.8 27B? (merged after 17h of development) quants: https://huggingface.co/ggml-org/Qwen3.8-Flash-Next-GGUF link to the previous discussion (I deleted the old post to avoid duplicates): https://www.reddit.com/r/LocalLLaMA/commen
Optional Bundle architecture: Schedule (session-local delayed / timed / interval reminders) was removed from the default set and made an explicit Optional Bundle. This cleanly separates “installed” from “enabled” and is the first systematic use of the Profile + Bundle model for official featur
Hey everyone! I’ve been working on ASTRABOX: an arcade interface where you describe a game, the AI builds it, and you can ask for changes by voice while playing. Each game gets its own visuals and gameplay, while a shared runtime handles controllers, scores, player joining, etc. I built it aro
We had a Dell B300 in the lab for a few weeks and used it to create two fine tunes of Qwen Flash Next. Victoria (coding and agents) Qwen3.8-Flash-Next cut down by 44% using a paper / technique called REAP: 512 down to 288 per layer. Retrained at 4-bit (NVFP4) afterwards, so it's trained for the for
submitted by /u/paranoidray [link] [comments]
I'm part of the BiliBili Index LLM team. We're sharing Index-Translate and its companion models for translating text, documents, and videos. Index-Translate supports 150 text languages, with 2B, 9B, and 35B-A3B (preview) options. You can specify terminology, writing style, and output format—for exam
submitted by /u/paf1138 [link] [comments]
submitted by /u/TuskNaPrezydenta2020 [link] [comments]
Ling-3.1-flash: ~560B total params, ~25B active/token, up to 1M-token context. Across work, coding & healthcare: 1,673 Elo on GDPVal-AA v2.1, 75.16 on FrontierSWE, and 65.35 on HealthBench Professional. submitted by /u/Elouakili_Flexy [link] [comments]
I've been closely following the rise of the Strata inference engine and as someone with 28GB VRAM and 32GB RAM I'm itching to buy 32GB more RAM just to use Flash Next. But of course before I make such a financial commitment as a member of the GPU-poor class like myself, first I need to make sure the
There's so many new techniques like RL, RL LoRA, QLoRA, CPT LoRA. I believe i would have a usecase for them, but i don't know where to learn, youtube is filled with bad quality tutorials if i just search and the good channels (fireship, bycloud) don't cover these as they're quite new concepts, i gue
loss curve (taken from the last micro of every step, to explain the variation) some help from gemini 3.8 flash high About 40% of the way done with the initial fine tune. The loss is so spiky because I accidentally used the last loss of each micro, rather than the average of each step The train
"AREX-2 is a 27B-parameter long-horizon agent model from the Beijing Academy of Artificial Intelligence (BAAI). It learns to improve a solution over multiple test-time rounds: propose, measure, reflect, and revise. AREX-2 is trained on machine-learning and algorithmic-programming tasks with ve
26 months ago Liang Wenfeng said: "Someone must step onto the frontier." Now they are training their models on Ascend 950 submitted by /u/WebAssemblyMan [link] [comments]
Disclaimer: Any* means any model that exposes its CoT without it being censored. Hey guys - half a tutorial/guide, and half an I built this, so I went for resources. This is something that I created for myself recently when I couldn't find any good existing solution. I wrote this post myself,
I started mapping the building blocks shared across all the models in audio.cpp. The result ended up being more interesting than I expected. Qwen has become by far the most common language backbone in this collection: 32 audio model families use a Qwen-family architecture, and 20 of them use Q
I know I sound crazy, but i’m using a strix halo and finding that GLM 4.7 flash just runs significantly better than qwen 3.6 35 a3b. But its obviously quite old at this point, i wish we had a new glm that was 4.7 flash sized but is anyone using a model that they have found better than this. My brief
Thanks to tcclaviger, vLLM now has expert RAM offloading support (link). This makes frontier models much more accessible on a local setup! I was able to run the original DeepSeek-V4-Flash-Vision-Exp on four R9700s. podman run --rm -it \ --init \ --network host \ --ulimit memlock=-1:-1 \ -v /mo
submitted by /u/brown2green [link] [comments]
I'm running Qwen 3.8 27B Q4 XS with ~30 t/s decode (no MTP) at 100k context with q8/q5 KV cache on a 16GB AMD GPU. I wanted to share my setup since many believe Qwen 3.8 27B to be infeasible on 16GB VRAM. Build llama.cpp with Vulkan: cmake -B build -DGGML_VULKAN=ON && cmake --build build --config Re
IQuest-Q1 is a Mixture-of-Experts (MoE) model developed by IQuest for agentic coding, reasoning, and multi-step tool use. It comprises approximately 320B total parameters, with an estimated 15B parameters activated per token. submitted by /u/jacek2023 [link] [comments]
I’m building a Polish General purpose legal Model that drafts documents, answers questions using legal sources, and has enough coding ability to handle some automation. The workflow is very tool-heavy: Question → many sequential tool calls → final answer/document Think Claude Code/Codex-style execut
First 3 disposition results. Hi there! My name is Jerry and I recently built Enclosure, e deterministic environment for testing LLMs. It's a simulated office enfironment https://github.com/openconstruct/Enclosure with tools agents are used to, like slack, calendar, mail, chat and more. For con
Here's a metric dashboard giving an idea of the last few days. Been testing with a variety of different agentic coding use-cases, mostly using a pi harness. qwen3.8-flash-next has seriously exceeded my expectations (used https://huggingface.co/tcclaviger/Qwen3.8-Flash-Next-MXFP4-FP8) Both spee