Search: “engineering”

Xiaomi released and open-sourced MiMo-V2.5-Pro, delivering significant improvements over its predecessor in agentic capabilities, complex software engineering, and long-horizon tasks. The model is an

Blog Post : ML Drift: Next-Gen GPU AI/ML Inference at the Edge - Google Developers Blog The Google AI Edge Team is excited to announce the open-source release of ML Drift, our high-performance, cross-

At my company, we’re using GLM-5.3 Flash internally for software engineering work, and I’ve been genuinely impressed by it. I work in a very large production environment with projects totaling **milli

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

The opponent plans by simulation: every second it scores each candidate play by running the match 10 seconds ahead in the engine. Our PPO agent learned to park its Cannon behind its own King. Losing a

Today I present a fine piece of engineering, carefully assembled inside a custom chipboard chassis: the 2400cc Inference Racer, a.k.a. my winter heater. Power comes from two second-hand AORUS RTX 3090

Hello Everyone! Good news for anyone who can compile code on apple, you can now experience using a AMD Radeon AI Pro R9700 on a MacBook Pro or Mac mini, Mac Studio or any OSX variant as long as it has

A while ago I posted 15 tok/s output and 100-120 tok/s prompt processing with the IQ3_XXS quant on a 12GB RTX 5070 using llama.cpp. Since then I built my own inference engine for this one model and th

onPanda is designed for geeks, power users, curious minds, and engineers. Its UI is built for deep exploration and efficient data annotation. - The core loop is simple: hover over a token → click an a

I released KaozKit this week, a Swift library for running LLM agents written in JavaScript inside a Mac app. Built from the start to keep everything local. Providers: MLX with Hugging Face model manag

I've been working on something that started as the training backend for my Hierarchos architecture, but it has grown into a much broader project: https://github.com/necat101/Hierarchos-Native Hierarch

Hey everyone — I’m building TensorSharp, an open-source LLM inference engine. Here are the latest DeepSeek V4.1 Flash GGUF results using its native ggml_cuda backend. Setup: 8× NVIDIA A40, layer split

Looking for tools to build/run an engine to do STT-LLM-TTS basically. I know how to run all of them separately, and if need be I can build one myself, but I was curious if there is already an open sou

The downside of uncensoring a model is that it is known to potentially damage it, but CyberTiel is an even more capable software engineer than its censored TielCoder base, while allowing offensive sec

Hi, I'm the co-creator of this Qwen3.8-Flash-Next engine support in MLX-serve. I've been tuning this one to run both fast, efficient and correct up 1m context using kv cache 8 bits in M5 Max 128GB. Qw

DISCLAIMER I ramble a lot and am not good at focusing on documentation and or coherent thoughts. TLDR I did things I made a thing and it works for me. I will try to answer any questions. A few people

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

I’ve been experimenting with neural rendering outside a game engine and built a native Windows video player around it. It prepares a neural-rendered version of a video, caches it, and lets you switch

I’ve been experimenting with MiniMax H3 and finally have video generation working in TensorSharp. TensorSharp started primarily as a local GGUF/LLM inference engine, so getting a video-generation pipe

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

Sharp v22.1 is u/peculiar-ragdoll's system prompt that makes Qwen answer way more tersely without losing correctness. NInfer is a hyper-tailored inference engine that only runs certain Qwen models on

This post was made with AI. I tried to remove as much slop as possible and keep it straight to the point to save your time as I know how annoying AI slop posts can be, but I still wanted to retain all

This is a HANDWRITTEN post. I spent way too much time trying to get fast inference on Apple Silicon. This post is for people who want to know what's the latest on running local models on their mac, an

Hey everyone ! Quick share from the cyber + local LLM side of things that I found interesting. During this week’s hacker summer camp, an AI researcher and reverse malware engineer veteran 'lordx64' on

As you all know the model is 2.69B parameters with a 128K context window and purpose-built for multi-step agent workflows. What you are seeing is the Q4_K_M GGUF running on my own inference engine bui

Hi all, I'm happy to announce that Xberg v1 is out. Xberg is the successor to Kreuzberg, equivalent to what would have been Kreuzberg v5. It's a content intelligence framework that handles a very wide

I'm an avid user of Deepseek v4 Flash via antirez's DS4 DwarfStar inference engine, and so when the new checkpoint dropped, the first thing I did was rent a cloud box and spin up a quantization for us

A r/ChatGPT post by a software engineer with 7 years of experience offering practical advice to 'vibe coders' — developers who use AI tools to generate code with minimal traditional programming knowle

This Reddit post from r/MachineLearning announces a build-from-scratch Python book focused on the engineering infrastructure surrounding AI systems — the components beyond the model call itself, such

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

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

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

LemonSeed Studio is an iPad editor/IDE with on-device inference on an AMD GPU in a Thunderbolt enclosure. It embeds the unmodified upstream Linux amdgpu + amdkfd driver (mac_linuxgpu) as a PCIDriverKi

I've been tinkering with GLM-5.3-Flash on two 64GB CMP 170HX cards for a while, and the setup is finally stable enough that I figured I'd share it. I also compared it against the Qwen3.8-Flash-Next se

I'm a Ai engineer with about 2 years work experience, but let's just assume that I was a undergraduate student just starting out where would I begin so that I can publish a A* conference paper at some

This is an update. I posted LocalMind here many moons ago from another account, when it was a Gemma chat in a tab. LocalMind is a static web page that runs models on your GPU through WebGPU. It has no

I've been working on an extension that runs MiniMax H3 inside Forge Neo. H3 makes the picture and the sound together, in one pass: footsteps, rain, engines, music and dialogue in pretty much any langu

Hi folks, LIVE PROJECT PAGE TLDR: Moral of the story. You need better CPU to do actual agentic coding doing real work... I've been on a mission to make my RTX5090 go brrr for past 2 months so much so

On my two DGX Sparks, Swift 1.5 (UkisAI's reasoning-efficient fine-tune of Qwen3.8-Flash-Next) running on veloGB10 (https://github.com/sf-stav/veloGB10, sf-stav's Rust/CUDA engine built only for GB10)

So I tried that miracle engine everyone is talking about. Asked the IQ3_S model to express its opinion on a post from this sub to measure the tps on a long-ish generation: Can you help with the follow

No click bait baby I promise - I'm live streaming the training process kinda like MiMo. Original thread: https://www.reddit.com/r/LocalLLaMA/comments/1wpg4a8/im_trying_to_posttrain/ If you didn't see

We built an inference engine for MoE models that don't fit in VRAM + RAM. Most of the model stays on the SSD, and experts are read as tokens need them. This started as a proof of concept, and poc work

I maintain TensorSharp, an open-source inference engine. It can now run Qwen-Image 2.1 locally for text-to-image generation and image editing, with support for its LoRA adapters. I’ve added configs fo

Jev from TypeSafe AI got me thinking about non-autoregressive decision engines, so I built a small proof-of-concept called AES to test the concept locally on open weights. It uses Qwen/Qwen2.5-1.5B-In

Hi all! i am currently working as a software engineer for a pretty big enterprise fintech company here in the states. In the the last 12 months at my job there has been a huge push for developers to u

We've been tuning vLLM/SGLang/llama.cpp setups for a long time and got tired of the profiling part: nsys trace, open the GUI, squint, change a flag, repeat. The profilers assume a human is looking at