Selora AI Local is an open-source, Qwen-based model for Home Assistant. Specs: Qwen3 1.7B base model (Q6 quantized~1.6GB) Four Home Assistant-specific LoRA adapters: - Answers - Clarifications - Automations - Commands ~3.5 GB total downloa…
model
Qwen3-0.6B
huggingface.co/Qwen/Qwen3-0.6B ↗
15189206 downloads1189 likestext-generationtransformers
from the model card
Qwen3-0.6B Qwen3 Highlights Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features: Uniquely support of seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue) within single model, ensuring optimal performance across various scenarios. Significantly enhancement in its reasoning capabilities, surpassing previous QwQ (in thinking mode) and Qwen2.5 instruct models (in non-thinking mode) on mathematics, code generation, and commonsense logical reasoning. Superior human preference alignment, excelling in creative writing, role-playing, multi-turn dialogues, and instruction following, to deliver a more natural, engaging, and immersive conversational experience. Expertise in agent capabilities, enabling precise integration with external tools in both thinking and unthinking modes and achieving leading performance among open-source models in complex agent-based tasks. Support of 100+ languages and dialects with strong capabilities for multilingual instruction following and translation. Model Overview Qwen3-0.6B…
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Show HN: Selora – local model for Home Assistant (github.com via hn) Show HN: FlashQwen – A from-scratch CUDA inference engine for Qwen3 (github.com via hn) We read every piece of feedback, and take your input very seriously. To see all available qualifiers, see our documentation.
Code Correctness Signals in LLM Hidden States: Pre-Generation Probing and Repair Geometry (arxiv.org) Large language models encode rich information in their hidden states. This work asks whether code correctness is legible in the hidden states of Qwen3-4B-Instruct-2507, before it generates and as it repairs a failed attempt, studied on 444…
Local LLM good for OCR of handwriting? (www.reddit.com via reddit) I am using qwen3-vl:8b and ollama for doing OCR on scans of handwritten letters and it is doing a decent job. Any other models I should know about for this kind of OCR?
Been testing agent skills frameworks for a week - the /spec before code rule is the actual game changer (www.reddit.com via reddit) I've been trying out the agent-skills pattern that's trending on GitHub (addyosmani/agent-skills, obra/superpowers) and what surprised me most isn't the slash commands or the auto-routing. It's the /spec before code rule.
Levi: Run AlphaEvolve on your local QWEN 30B (www.reddit.com via reddit) Hi r/LocalLLaMA, Wanted to share something I'm excited about. I've been fascinated by AlphaEvolve and its results for more than a year now, but running the open source frameworks gets expensive fast.
Looking for a local "NotebookLM for lawyers" setup – what am I doing wrong? (www.reddit.com via reddit) Hello everyone I am totally new to LocalLLMs and only used chatGPT/Claude/NotebookLM before. So bear with me 😃 I'm an attorney and would like to analyze and summarize case files locally for privacy/confidentiality reasons.
Initial testing with llama-bench and 3 different Qwen3 models for my R9700 32GB (www.reddit.com via reddit) In a recent build I did I used dual R9700 32GB cards but I wanted to see how a single R9700 stacked up against other hardware I had access to. I created a simple benchmark with llama-bench and ran it on a few different setups.
Tuning CPU-only Qwen3-30B inference with an IBM Quantum sampling loop (github.com via hn) Qwen Air QPU/MCP Lab Quantum-enhanced autoresearch for high-performance, CPU-only Mixture-of-Experts LLM inference on legacy hardware. This repository contains the benchmark harness, MCP-style tool boundary, experiment logs, paper draft, a…
Turning every "no thats not what i meant" in chat into actual LoRA training data (www.reddit.com) i kept running local models on my own hardware, they'd say something dumb, id sit there going "no thats not what i meant", id close the chat and the model never learned. so i built the correction loop into a desktop app.
My pipeline for the best speech to transcript results (www.reddit.com) I wished the new ASR (automatic speech recognition) models to give me the accurate output but I was disappointed, specially when the input was multilingual and noisy (all my use cases). I had to put in significant efforts in audio pre/post…
I ran a quantization shootout on Qwen3-Coder and the results are... interesting (www.reddit.com) Out of random curiousity I ran a shootout on Qwen3-Coder-Next. I've been using the MXFP4_MOE from unsloth for awhile as it's just really fast on my system.
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Seeking resources to read about llama.cpp server and how offloading works (www.reddit.com) SETUP INFO: Amd R9700 AI PRO. Using llama-cpp server, ROCM docker version.
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New Release of ROCm based MLX LLM Engine - lemon-mlx-engine (www.reddit.com) Hey everyone lemon-mlx-engine just got done integrating TheRock / ROCm 7.13 into the lemon-mlx-engine which means you get to try the latest ROCm on your local hardware with the MLX engine! This also includes various bug fixes and kernel fi…
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Built a personal Jarvis-style AI using MCP and open models (www.reddit.com) Still heavily work in progress, but I finally built a personal Jarvis-style AI using MCP and open models. It currently supports memory, autonomous file editing, visible tool-call tracing, confirmation before dangerous actions, persistent c…
As of May 2026 LongCat Dit 3.5B and Moss TTS 8B are the best SOTA tts models and Qwen tts is not even close. (www.reddit.com) [Disclaimer: i am totally avoiding fish audio s2 pro because its not a real open-sourced model(non commercial license)] So the context is i asked many ai to give me best tts model as of now but most of it said qwen 3 tts, and voxtral etc.…
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Two flat-fee agent endpoints, no token meter: OpenClaw chat ($7/mo, 128K ctx) + All You Can Code ($19/mo, 256K ctx). OpenAI v1. (www.reddit.com) For anyone running agents (coding or otherwise) who'd rather pay a flat fee than meter tokens. Two tiers, both flat fee, both unlimited: OpenClaw ($7/mo) - Nemotron-3-Nano-Omni-30B-A3B - 128K context - For general-purpose agents: research,…
I trained TIME: short context-triggered thinking on Qwen model instead of overthinking (www.reddit.com) Started this as a personal project for my Open-WebUI setup to use. Somehow it ended up as an ACL 2026 paper.
MiroThinker-1.7, an open-weight deep research agent (Qwen3 MoE base) — mini is 30B/3B active, curious what tok/s people get on consumer hardware (www.reddit.com) As usual, disclosure first: I'm on the team that built this. Our MiroThinker-1.7-deepresearch and 1.7-mini-deepresearch API went live, mini is a deep research agent built on Qwen3 MoE (30B total, 3B active for mini).
How are you all handling state for long-running agents? Stateless sandboxes are eating my evenings (www.reddit.com) ok I want to know if I am the only one. been running a local coding agent against qwen3 coder on a 4090 box, with a remote sandbox for the actual code execution.
Case Study: Dogfooding a Facebook Agent Before Deploying It to a Realtor (www.reddit.com) A real estate firm came to us wanting an AI agent that could run their Facebook page. Not a scheduler.
Came home to find Pi with Qwen3.627B had run rm -rf ..... (www.reddit.com) on the build cache because it had run my computer out of disk space. So I assign my coding agent (pi) a task, and then leave the house.
Predicting Rare LLM Failures with 30× Fewer Rollouts (www.lesswrong.com via hn) TL;DR: We estimate how often Qwen 3 4B exhibits rare harmful behaviors with 30× fewer rollouts than naive sampling, using a new method that interpolates between the model and a less-safe variant in logit space. Authors: Francisco Pernice (…
Qwen/WebWorld 32B/14B/8B (Qwen3 finetune) (www.reddit.com) WebWorld is a large-scale open-web world model series for training and evaluating web agents. It is trained on 1M+ real-world web interaction trajectories via a scalable hierarchical data pipeline, supporting: Long-horizon simulation (30+…
Code's open. Tried building a fully real time on-device voice assistant + live translator on a phone (multilingual, STT→LLM→TTS, all local) on the Tether QVAC SDK. (www.reddit.com) Wanted to see if a real voice loop — speak, model thinks, speaks back — could run entirely on a single device today, no cloud. Same codebase doubles as a live translator (speak in language A, hear it back in language B).
Show HN: Per-request emotion steering for vLLM, with batching preserved (github.com via hn) emotion-steering Extract and serve CAA-style emotion steering vectors for any HuggingFace causal LM, with a fast vLLM path for Qwen3. ┌────────────┐ ┌────────────────────┐ labeled │ extract │ vectors + AUC report │ serve │ contrasts ├─────…
A Qwen finetune, that feels VERY human (www.reddit.com) Hello guys, So TL;DR, I was asked by multiple people to make an Assistant_Pepe_32B version, but the best base model contender was Qwen3-32B, a model that is very hard to tune on anything other than STEM. The concept of Assistant_Pepe is an…
[Paper on Hummingbird+: low-cost FPGAs for LLM inference] Qwen3-30B-A3B Q4 at 18 t/s token-gen, 24GB, expected $150 mass production cost (dl.acm.org via reddit) dl.acm.org Performing security verification This website uses a security service to protect against malicious bots. This page is displayed while the website verifies you are not a bot.
Looking for Small VLM/MLLMs Alternatives to Qwen Series Models (www.reddit.com) I have tried Qwen 3 VL family of models on my rtx3060, max I can load is Q8 8b. The task is visual reasoning/ instruction following.