๐Ÿ”ด High Significance

Model Releases

๐Ÿ”ด ๐Ÿ’ฌ I have DeepSeek V4 Pro at home โ€” score 88 Sources: reddit/r/LocalLLaMA

Just wanted to share that I used u/LegacyRemaster slightly modified (Q4_K_M conversion support) DeepSeek V4 CUDA repo (based on u/antirez work) to convert and run Q4_K_M [De

๐Ÿ”ด ๐Ÿ’ฌ How I set up an AI agent to handle invoicing bill pay and expense tracking through my bank via MCP โ€” score 83 Sources: reddit/r/AIAgents

I run a B2B lead gen agency and was spending hours a week on invoicing clients, paying contractors, tracking expenses and bookkeeping. Wanted to automate the financial operations side so I could focus on actual client work and heres how I set it up and what I learned. The setup: I use Meow for banki

Developer Tools

๐Ÿ”ด ๐Ÿ™ NousResearch/hermes-agent โ€” The agent that grows with you โ€” score 99 Sources: github_trending

The agent that grows with you

๐Ÿ”ด ๐Ÿ’ฌ Tokens are not positively correlated with Quality and should not be a success metric โ€” score 94 Sources: reddit/r/AIAgents

I think Anthropic and OpenAI have successfully turned token consumption into a status symbol. Like itโ€™s somehow a metric of productivity. Iโ€™ve been building agents since 2022 for my own projects, SMBs, and government clients. Iโ€™ve been using LangChain since Harrison was running the Discord and the c

๐Ÿ”ด ๐Ÿ™ anthropics/skills โ€” Public repository for Agent Skills โ€” score 82 Sources: github_trending

Public repository for Agent Skills

๐Ÿ”ด ๐Ÿ™ yikart/AiToEarn โ€” Let's use AI to Earn! โ€” score 77 Sources: github_trending

Let's use AI to Earn!

๐Ÿ”ด ๐Ÿ’ฌ AI meeting assistants make more sense once you use them as agent input โ€” score 72 Sources: reddit/r/AIAgents

I used to think AI meeting tools were mostly just smart note takers, but lately Iโ€™ve been looking at them differently. Whatโ€™s been more useful for me is having meeting context automatically saved and searchable later, transcripts, summaries, action items, decisions, all in one place. Iโ€™ve been using

Research Papers

๐Ÿ”ด ๐Ÿค— MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation โ€” score 95 Sources: huggingface

With the rise of online dance-video platforms and rapid advances in AI-generated content (AIGC), music-driven dance generation has emerged as a compelling research direction. Despite substantial progress in related domains such as music-driven 3D dance generation, pose-driven image animation, and au

Other Signals

๐Ÿ”ด ๐Ÿงก Local AI needs to be the norm โ€” score 88 Sources: hackernews

๐Ÿ”ด ๐Ÿ’ฌ Openclaw ia trending down and will disappear soon โ€” score 81 Sources: reddit/r/LocalLLaMA

๐Ÿ”ด ๐Ÿ’ฌ PhD students in ML, how many hours on average do you work? [D] โ€” score 81 Sources: reddit/r/MachineLearning

I generally work around 9โ€“10 hours a day, but not contiguously. I can usually carve out a dedicated chunk of time in the morning, take lab or project meetings in the afternoon, and block out around 6โ€“8 PM for commute, exercise, socializing, and dinner. I also get more work done in the evening, since

๐Ÿ”ด ๐Ÿ’ฌ Getting a feel for how fast X tokens/second really is. โ€” score 76 Sources: reddit/r/LocalLLaMA

I love following all your adventures with local LLM setups. Quality and size of the models are important, but so is performance. Numbers don't really convey the experienced speed well, however. If someone claims they run Qwen 3.6-27B at 21 tokens/second, how fast is that? Is 10 tokens/second unusabl

๐Ÿ”ด ๐Ÿ’ฌ Running Qwen3.6 35b a3b on 8gb vram and 32gb ram ~190k context โ€” score 73 Sources: reddit/r/LocalLLaMA

If anyone is looking for a good high-speed setup with ~190k context, this config has been working insanely well for me. Iโ€™m using my laptop as a server over Tailscale. Installed Linux on it and running: - Qwen3.6 35B A3B - RTX 4060 8GB VRAM - 32GB DDR5 5600MHz RAM - Q5 quant models Current mode

๐ŸŸก Notable

Model Releases

๐ŸŸก ๐Ÿ’ฌ Any implementations similar to D4RT? [D] โ€” score 56 Sources: reddit/r/MachineLearning

Deepmind released a paper on D4RT at the start of this year which crucially enabled a โ€œ4Dโ€ understanding of the world via structure from motion and generating: 1. Point cloud reconstruction from 2D videos (not static scenes) 2. Camera pose estimation You could pass in a video of a dog walking on a b

๐ŸŸก ๐Ÿ’ฌ Put my 4 years of SEO experience into a claude skill so you don't have to figure it out yourself โ€” score 56 Sources: reddit/r/AIAgents

I condensed my SEO experience into a Claude Code skill that actually does keyword research and writes articles the right way & open sourced it Most AI writing tools I came across gave really shallow output. They go straight from keyword to article with no research in between. No competitor analy

๐ŸŸก ๐Ÿ’ฌ ExLlamaV3 Major Updates! โ€” score 42 Sources: reddit/r/LocalLLaMA

Turboderp has a been on an absolute tear recently, in the endless battle to cram new llamas into smaller, faster boxes. We started off last month with the release of [gemma 4 support](https://github.com/turboderp-org/exllamav3/releases/tag/v0

Developer Tools

๐ŸŸก ๐Ÿ™ open-webui/open-webui โ€” User-friendly AI Interface (Supports Ollama, OpenAI API, ...) โ€” score 64 Sources: github_trending

User-friendly AI Interface (Supports Ollama, OpenAI API, ...)

๐ŸŸก ๐Ÿงก An AI coding agent, used to write code, needs to reduce your maintenance costs โ€” score 62 Sources: hackernews

๐ŸŸก ๐Ÿ’ฌ How are you operating local AI agents after the first demo works? โ€” score 56 Sources: reddit/r/AIAgents

Iโ€™m curious how other people here are handling the operational side of local/self-hosted agents. The demo phase is usually fun: wire a model to tools, get it to use a browser or files or an MCP server, watch it complete a task. But the next phase gets messy fast: - what agents are installed? - what

๐ŸŸก ๐Ÿ™ tinyhumansai/openhuman โ€” Your Personal AI super intelligence. Private, Simple and extremely powerful. โ€” score 56 Sources: github_trending

Your Personal AI super intelligence. Private, Simple and extremely powerful.

๐ŸŸก ๐Ÿ™ ZhuLinsen/daily_stock_analysis โ€” LLM้ฉฑๅŠจ็š„ A/H/็พŽ่‚กๆ™บ่ƒฝๅˆ†ๆž๏ผšๅคšๆ•ฐๆฎๆบ่กŒๆƒ… + ๅฎžๆ—ถๆ–ฐ้—ป + LLMๅ†ณ็ญ–ไปช่กจ็›˜ + ๅคšๆธ ้“ๆŽจ้€๏ผŒ้›ถๆˆๆœฌๅฎšๆ—ถ่ฟ่กŒ๏ผŒ็บฏ็™ฝๅซ–. LLM-powered stock analysis system for A/H/US markets. โ€” score 51 Sources: github_trending

LLM้ฉฑๅŠจ็š„ A/H/็พŽ่‚กๆ™บ่ƒฝๅˆ†ๆž๏ผšๅคšๆ•ฐๆฎๆบ่กŒๆƒ… + ๅฎžๆ—ถๆ–ฐ้—ป + LLMๅ†ณ็ญ–ไปช่กจ็›˜ + ๅคšๆธ ้“ๆŽจ้€๏ผŒ้›ถๆˆๆœฌๅฎšๆ—ถ่ฟ่กŒ๏ผŒ็บฏ็™ฝๅซ–. LLM-powered stock analysis system for A/H/US markets.

Omitted 3 additional developer tools items from the main section; see raw data and source-specific sections below.

Infrastructure & Compute

๐ŸŸก ๐Ÿ™ jundot/omlx โ€” LLM inference server with continuous batching & SSD caching for Apple Silicon โ€” managed from the macOS menu bar โ€” score 68 Sources: github_trending

LLM inference server with continuous batching & SSD caching for Apple Silicon โ€” managed from the macOS menu bar

Enterprise Adoption

๐ŸŸก ๐Ÿข How enterprises are scaling AI โ€” score 50 Sources: lab_blog/OpenAI

How enterprises scale AI: from early experiments to compounding impact through trust, governance, workflow design, and quality at scale.

Research Papers

๐ŸŸก ๐Ÿค— Rethinking State Tracking in Recurrent Models Through Error Control Dynamics โ€” score 68 Sources: huggingface ยท arxiv/cs.CL

The theory of state tracking in recurrent architectures has predominantly focused on expressive capacity: whether a fixed architecture can theoretically realize a set of symbolic transition rules. We argue that equally important is error control, the dynamics governing hidden-state drift along the d

๐ŸŸก ๐Ÿค— Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning โ€” score 60 Sources: huggingface ยท arxiv/cs.AI

Fast Weight Programmers (FWPs) encode temporal dependencies through dynamically updated parameters rather than recurrent hidden states. Quantum FWPs (QFWPs) extend this idea with variational quantum circuits (VQCs), but existing implementations rely on multi-qubit architectures that are difficult to

Other Signals

๐ŸŸก ๐Ÿ’ฌ MTP benchmark results: the nature of the generative task dictates whether you will benefit (coding) or get slower inference (creative) from speculative inference. No other factor comes close. โ€” score 65 Sources: reddit/r/LocalLLaMA

I recently published MTP quants of Qwen 3.6 27B and I was suprised by the reports here on reddit, and on HF, of users who were experiencing worst speed with speculative inference than without. Th

๐ŸŸก ๐Ÿ’ฌ I Think I Spent Way Too Much Time Messing with Local LLMs โ€” score 58 Sources: reddit/r/LocalLLaMA

Guys, I'm hearing coil whine in my sleep. Help >!/s!<

๐ŸŸข Incremental

Model Releases

๐ŸŸข ๐Ÿ’ฌ What's actually moving the needle on agent token bills? โ€” score 39 Sources: reddit/r/AIAgents

I've been researching how teams handle FinOps and cost optimization on agentic workflows in production. wanted to share what keeps coming up and ask what's actually working in your setup. Most stacks I've looked at have the same starting kit. cheaper model for routing or sub-tasks (haiku, gpt-4o-min

๐ŸŸข ๐Ÿงก How Fast Does Claude, Acting as a User Space IP Stack, Respond to Pings? โ€” score 38 Sources: hackernews

๐ŸŸข ๐Ÿ’ฌ The Qwen 3.6 35B A3B hype is real!!! โ€” score 35 Sources: reddit/r/LocalLLaMA

My personal test for small local LLM intelligence is to check whether a model has any ability to understand the code that I write for my own academic research. My research is on some pretty niche topics and I doubt that anything like it is substantively present in the training sets for LLMs. A few m

๐ŸŸข ๐Ÿงก Show HN: adamsreview โ€“ better multi-agent PR reviews for Claude Code โ€” score 12 Sources: hackernews

Developer Tools

๐ŸŸข ๐Ÿ™ MemoriLabs/Memori โ€” Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. โ€” score 39 Sources: github_trending

Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems.

๐ŸŸข ๐Ÿ™ apify/crawlee โ€” Crawleeโ€”A web scraping and browser automation library for Node.js to build reliable crawlers. In JavaScript and TypeScript. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with Puppeteer, Playwright, Cheerio, JSDOM, and raw HTTP. Both headful and headless mode. With proxy rotation. โ€” score 30 Sources: github_trending

Crawleeโ€”A web scraping and browser automation library for Node.js to build reliable crawlers. In JavaScript and TypeScript. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with Puppeteer, Playwright, Cheerio, JSDOM, and raw HTTP. Both headf

๐ŸŸข ๐Ÿ’ฌ Has anyone built scripts or seeded test workspaces for Gmail, Slack, Teams, Notion, GitHub etc.? โ€” score 17 Sources: reddit/r/AIAgents

We're building an AI agent platform and need realistic test environments across a bunch of SaaS tools. Empty sandboxes don't cut it โ€” we need accounts that look like they've actually been used. Specifically looking for any of the following: * Scripts that use APIs to seed realistic data (emails,

๐ŸŸข ๐Ÿ’ฌ Would you trust an AI agent to monitor flight deals and book them for you? โ€” score 17 Sources: reddit/r/AIAgents

I joined a startup team, because everyone on the team shares the same travel frustration: thereโ€™s just no time to keep checking flight apps every day. A lot of flight alert tools are too slow. Sometimes airlines or travel platforms briefly show unusually low fares or even prices caused by a system b

๐ŸŸข ๐Ÿ’ฌ Why your AI agent needs a dedicated inbox, not a shared mailbox (and how to wire it up) โ€” score 17 Sources: reddit/r/AIAgents

Been building agent workflows that send and receive email for a while now. One of the most common mistakes I see is routing all agent email through a single shared inbox like [email protected] or a team Gmail account. # The problem with shared inboxes # When your agen

Omitted 2 additional developer tools items from the main section; see raw data and source-specific sections below.

Research Papers

๐ŸŸข ๐Ÿค— Sparse Autoencoders as Plug-and-Play Firewalls for Adversarial Attack Detection in VLMs โ€” score 38 Sources: huggingface ยท arxiv/cs.AI

Vision-language models (VLMs) have advanced rapidly and are increasingly deployed in real-world applications, especially with the rise of agent-based systems. However, their safety has received relatively limited attention. Even the latest proprietary and open-weight VLMs remain highly vulnerable to

๐ŸŸข ๐Ÿค— R^3-SQL: Ranking Reward and Resampling for Text-to-SQL โ€” score 25 Sources: huggingface

Modern Text-to-SQL systems generate multiple candidate SQL queries and rank them to judge a final prediction. However, existing methods face two limitations. First, they often score functionally equivalent SQL queries inconsistently despite identical execution results. Second, ranking cannot recover

Other Signals

๐ŸŸข ๐Ÿ’ฌ unsloth/MiMo-V2.5-GGUF ยท Hugging Face โ€” score 27 Sources: reddit/r/LocalLLaMA

can you run it?

๐ŸŸข ๐Ÿ’ฌ Any news (or hope) of Qwen-3.6 14B and 9B distills for local coding ? โ€” score 12 Sources: reddit/r/LocalLLaMA

As the title suggests. I'm already testing (with some success, and few challenges) usage of Qwen-3.5 9B with a new work laptop that I've received with RTX 1000 6GB VRAM (I know it seems like a joke in today's time and age). I am using it with `pi` as the terminal coding harness. The issue I am fac

๐ŸŸข ๐Ÿ’ฌ Why is human LLM annotation so expensive? [D] โ€” score 6 Sources: reddit/r/MachineLearning

Scale AI and similar services charge a lot for annotation. MTurk is cheap but the quality is horrible for anything requiring real domain understanding. For small teams that need a few thousand labeled examples to calibrate their evals or fine tune a model, there seems to be no good middle ground. Ho

๐ŸŸข ๐Ÿ’ฌ Has anyone been able to get Draft Models to load in LM Studio? โ€” score 4 Sources: reddit/r/LocalLLaMA

Per title. Been trying to load Gemma E2b as draft model for 26b as target using LM Studio's UI but it can't seem to recognise what's already been downloaded. Any advice on how to get this to work?

RepoDescriptionStars TodayLanguage
NousResearch/hermes-agentThe agent that grows with you1496python
anthropics/skillsPublic repository for Agent Skills509python
yikart/AiToEarnLet's use AI to Earn!397typescript
jundot/omlxLLM inference server with continuous batching & SSD caching for Apple Silicon โ€” managed from the macOS menu bar185python
open-webui/open-webuiUser-friendly AI Interface (Supports Ollama, OpenAI API, ...)174python
tinyhumansai/openhumanYour Personal AI super intelligence. Private, Simple and extremely powerful.154rust
ZhuLinsen/daily_stock_analysisLLM้ฉฑๅŠจ็š„ A/H/็พŽ่‚กๆ™บ่ƒฝๅˆ†ๆž๏ผšๅคšๆ•ฐๆฎๆบ่กŒๆƒ… + ๅฎžๆ—ถๆ–ฐ้—ป + LLMๅ†ณ็ญ–ไปช่กจ็›˜ + ๅคšๆธ ้“ๆŽจ้€๏ผŒ้›ถๆˆๆœฌๅฎšๆ—ถ่ฟ่กŒ๏ผŒ็บฏ็™ฝๅซ–. LLM-powered stock analysis system for A/H/US markets.141python
MemoriLabs/MemoriMemori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems.62python
apify/crawleeCrawleeโ€”A web scraping and browser automation library for Node.js to build reliable crawlers. In JavaScript and TypeScript. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with Puppeteer, Playwright, Cheerio, JSDOM, and raw HTTP. Both headful and headless mode. With proxy rotation.42typescript
alibaba/page-agentJavaScript in-page GUI agent. Control web interfaces with natural language.12typescript

๐Ÿ“„ New Papers

TitleCategoryHotnessLink
MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generationresearch_paper70Open
Rethinking State Tracking in Recurrent Models Through Error Control Dynamicsresearch_paper7Open
Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learningresearch_paper3Open
GraphDC: A Divide-and-Conquer Multi-Agent System for Scalable Graph Algorithm Reasoningcs.AI0Open
More Thinking, More Bias: Length-Driven Position Bias in Reasoning Modelscs.AI0Open
Fast and Effective Redistricting Optimization via Composite-Move Tabu Searchcs.AI0Open
State Representation and Termination for Recursive Reasoning Systemscs.AI0Open
Hidden Coalitions in Multi-Agent AI: A Spectral Diagnostic from Internal Representationscs.AI0Open
CASCADE: Case-Based Continual Adaptation for Large Language Models During Deploymentcs.AI0Open
From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanismscs.AI0Open
When Does a Language Model Commit? A Finite-Answer Theory of Pre-Verbalization Commitmentcs.AI0Open
Weblica: Scalable and Reproducible Training Environments for Visual Web Agentscs.AI0Open
When Does Critique Improve AI-Assisted Theoretical Physics? SCALAR: Structured Critic--Actor Loop for Agentic Reasoningcs.AI0Open
Towards Security-Auditable LLM Agents: A Unified Graph Representationcs.AI0Open
Uneven Evolution of Cognition Across Generations of Generative AI Modelscs.AI0Open

๐Ÿข Lab Blog Posts

Repeated From Recent Briefings