Search: “model-releases”

Below are the benchmark results for running Qwen3.8-Flash-Next on Strix Halo using the Vulkan backend of llama.cpp, combined with MTP model. Hardware Item Details CPU AMD Ryzen AI MAX+ 395 (16C/32T) G

~20–30GB smaller than Unsloth/AesSedai Q4 at similar PPL. After several days of testing I released a set of mainline-compatible imatrix quants for Qwen3.8-Flash-Next. Goal: same quality band as the po

this model is really something incredible, saved us like 600 dollars. my fiance is always breaking her electronics and then getting me to fix them. The other day she brought me her phone and it was st

Announcement: https://www.tbench.ai/news/terminal-bench-4-0 Leaderboard: https://www.tbench.ai/ Imo the best aspect in their announcement is their focus on rapidly iterating on TerminalBench to keep t

The official benchmark card for Ling-3.0-flash-Fin is a useful reminder that the unit being tested is rarely just “the model.” The release says most runs used temperature 1, top_p 0.95 and the highest

I was running Ollama with Maxwell 1500, using a 65,536-token context window, through Zoo Code inside VS Code. I asked the model to analyze a folder containing some pretty simple code. It spent around

hi i make tool for this called llmog it's purpose to make llms free to - auto annotation datasets - reclassification existing yolo datasets running totally local using llama cpp or vllm or use externa

Quote: ... developing a new A.I. model intended to be as powerful as Anthropic’s cutting-edge models. ... In July, while developing Watermelon, Meta paused and later resumed a stage of A.I. developmen

Hey guys, FastVideo team here. We saw how important speed and quality is for everyone. And we've been working to create our own step distill checkpoints and LORAs for MINIMAX h3. Here's is our v1 rele

Hey, An LLM writing into durable memory is an unreliable author. It invents, mislabels, restates, and contradicts. Once one of those mistakes is saved, the agent can carry it into every conversation t

Model: unsloth/GLM-5.3-Flash-GGUF UD-Q2_K_XL (4 shards, 101 GiB) + mmproj-BF16. Reference: llama.cpp PR #27754 (glm5next), CUDA 12.8, SM 120. Throughput Both engines back to back in one session, flash

As in actual physical heat. How are people coping with the heat that running a decent inference rig pumps out? I've got dual 5060 Ti GPUs and a relatively modest CPU (Intel 14 Core Ultra 5 245KF Deskt

I dont know about others, but Nvidia seem to close the lid on older GPUs since they want to push their new technology. Llama and team has been the to go places for older GPUs like V100s. Knowing how N

TL;DR: k-quants need tensor rows divisible by 256. When they aren't, llama-quantize quietly swaps in a ~4.5 bpw type and the file keeps its low-bit name. I audited 443 quants across 25 repos; 64 are a

I built a benchmark called EchoNet. An agent gets a factual question, then searches a syntheic web I made before answering. Some of that web is seeded with misinformation: one fake page, a fake page r

Smaller models still struggle with browser tasks that require open-ended research or deep reasoning. But many practical browser-automation workflows are much more procedural: extracting structured dat

I've been running Qwen3-0.6B on the M5Stack LLM-8850 card (Axera AX8850 NPU, 24 TOPS, 8GB LPDDR4x) hosted by a Raspberry Pi 5 — as a llama.cpp backend. The problem: the vendor stack requires convertin

However, I keep getting a 404 error when trying to access qwen3.8-flash-next:125b-mlx and ornith-1.5:397b via the API, even though they are listed in the model list. Does anyone know why this is happe

The initial reason for this was the Comfy H3 Sync & Sound Community Challenge: Comfy H3 Sync Sound Community Challenge! - by Allyson Toy I made a short rap track in Suno, then used Hermes Agent to bui

I read this somewhere and wasn't sure if it's still an issue or if it only affects external models versus all models used via the Claude Code CLI. 'This latest Ollama update finally fixes that issue w

Using https://huggingface.co/RadixArk/Qwen3.8-Flash-Next-NVFP4 and https://old.reddit.com/r/BlackwellPerformance/comments/1w04xb7/qwen38_flashnext_on_1x_rtx_pro_6000_171_ts_c1_428/ As usual, all the d

Built the latest and I'm getting as much as 220 tokens per second and averaging in the 170s, I can't get over it. If anyone on here is on that project, fuckkkin' chapeau man, really incredible job. I

Proof is in the method honestly. Closed model labs need to constantly reinvent the wheel to keep lead. Open source has a bunch of independent labs practically working somewhat together. Eventually whe

A few days ago I posted asking what people considered the best local model for an 8 GB VRAM GPU. At the time, my personal sweet spot was Qwen3.6-35B-A3B, for agentic coding with Pi.dev. Well… Thanks t

I wanted to see whether NInfer could run Qwen3.8-27B on an RTX PRO 4000 Blackwell 24GB. Hardware/software: NVIDIA RTX PRO 4000 Blackwell, 24GB 145W power limit CUDA 13.3 NVIDIA driver 610.x Ubuntu LXC

EDIT: Though the issue with q8 kv cache seems to arise from when and how often we run the quantize step, not that kv quantizing can't ever work - see comments for various proposed solutions --- One of

TL;DR: llama.cpp with --load-mode mmap used 21-32 GB of RAM, with ik_llama.cpp using 106-108 GB. -sm tensor killed my prefill, changing to -sm layer went from 36 tps to 135 tps. After that, -ubatch 20

I've got Qwen3.8-Flash-next running on RTX 3090, Ryzen 9 3950X, a PCIe 3.0 motherboard, and 64GB DDR RAM from 2020. IQ4_XS weights, full kvarn5 context, vision on GPU, experts in host RAM, n-grams on

We're releasing Qwen3.8-27B quantized with our newest methods, GSQ + RCO. Higher-quality models, same file size, now with the search and the quantizer both learned. What's inside: GSQ (Gumbel-Softmax

Their last version 7.14 was released just a month ago. llama.cpp PR(waiting for approval) for Version 10.0 https://github.com/ggml-org/llama.cpp/pull/27803 Hope this version comes with more boost & im

Post rédigé avec l'aide de GLM5.3 flash Contexte : formateur professionnel d'adultes en France, j'utilise des agents LLM au quotidien et le français qu'ils produisent est mon critère n°1, avant les be

Hey all, and hello fellow DGX Spark-ers! Today I managed some pretty crazy numbers: 181 tok/s aggregate on 2× DGX Spark on Qwen3.8-Flash-Next at 512Kcontext (2.8M kvc) I hit 181 tok/s aggregate today

Hey everyone, I am the co-founder of Tontaube. My brother and I just released TontaubeV1, a 2.9B-parameter open-weight TTS model focused on expressive speech, long-form generation, and low-latency loc

After getting tired refreshing and searching sub reddits for qwen 3.8 35 a3b i decided to give qwen 3.8 flash next a try . So I dual booted and built llama cpp I am able to hit 6-7 tps constantly insi

ok bit more context: it's actually a QAT Q2 for Qwen 3.8 27 B: https://huggingface.co/sdkyuan/qwen3.8-27B-qat-q2_0-gguf QAT Q2 for DFlash model: https://huggingface.co/HermiHg/Qwen3.8-27B-DFlash2-Q2_K

Everything has changed in two months: DS4 0731 flash was the start of a wave that is taking open weights to paradise. It is easy to think that Qwen 4 and GLM 6 will be on par with Mythos. submitted by

I installed the Claude Desktop via the ollama Mac app. Unfortunately, no connectors or plugins can be installed or none are listed. Is that normal or is there no possibility there submitted by /u/amne

Spent yesterday getting Qwen3.8 Flash and GLM 5.3 Flash up and running on my cluster of 4 x DGX Sparks with a view to replacing DeepSeek 0731... but.. really not that impressed with GLM 5.3 - overly v

Repost because reddit keeps thinking this is piracy or illegal. It is neither. A lot of people are skeptical Nvidia will keep huggingface intact now that they will buy huggingface. There's a lot of do

The undocumented endpoint Everyone scraping the settings page for usage stats can stop. This works with your API key (the same Bearer you use for chat completions): curl -H 'Authorization: Bearer $OLL

Official Announcement: A First Look at Horus Cyber Nano 1.0 We are officially unveiling the first look at Horus Cyber Nano 1.0. This announcement presents the benchmark results of Horus Cyber Nano 1.0

I’ve been working on a small project called gemma4.c. The idea is pretty simple: you can download a modern language model, compile one 700-line C file, and have it generate text on an ordinary CPU. Th

Sharing my harness for running local LLMs that I built using Qwen 3.x 27B (> 90% locally built) under my supervision - not vibe-coded. Its free, no telemetry, and open-source (AGPL). Works on Windows,

I am sure for those of you who have been following my 4 step Krea 2 Turbo LoRA, you would know from my previous posts the work of progress I have been sharing with you ( if not see here - https://www.

Does anyone know of a decent reverse engineering harness/workspace setup for local models that I can just point the model at and have it go to work until it's reversed most if not all of the functions

HuggingFace releases microduck a 10 inch open-source biped with 15 actuators and sensors (camera, speaker, LiDAR, NFC, bluetooth, wifi, ...) that you train yourself with reinforcement learning, $400.