A new chapter for OpenClaw.
Your Mac is ready.
New conversations, memory, dashboards and automation. Explore the complete release guide, then get started with the compatible LocalClaw app.
OpenClaw 2.0 Is Here. LocalClaw Is Ready.
What’s new in 2026.8.1: conversations, memory, local inference, dashboards, approvals and experimental Swarm. Plus setup and updates on Mac.
Colibri Can Run GLM-5.2 on 25GB RAM. Here Is the Catch.
A tiny C engine streams 744B to 2.8T MoE models from NVMe. We explain the 9.9GB resident claim, 372GB footprint, real speed and hardware limits.
Kimi K3 Is Open Weight: Benchmarks and the Brutal Hardware Reality
The 2.8T Kimi K3 weights are public. We analyze the official scores, 1.56TB download, license and multi-node GPU requirements.
Qwen3.8-27B Is the Rare Model That Feels Bigger Than 27B
Native vision, 262K context, controllable reasoning and strong agentic results—inside one dense, Apache-2.0 checkpoint.
Bonsai 27B: Can a 27B Local AI Model Really Fit in 3.9GB?
PrismML compressed Qwen 3.6 27B into official 1-bit and ternary builds. Compare real size, RAM, quality, speed and runtime support.
Ornith 1.0 Is Out: Which Version Can You Run Locally?
DeepReinforce's new agentic coding family has 9B, 35B GGUF and 397B versions. Here is which one to run and how it compares with Qwen, GLM-5.2, DeepSeek and Gemma.
MisoTTS Is Here: Can You Run This 8B TTS Locally?
MisoTTS is an 8B emotive conversational voice model. Here is the honest hardware reality, local setup angle and best alternatives.
Qwen 3.7 Is Out: Can You Run It Locally?
Qwen 3.7 Max and Plus are real, but the local 27B open-weight model people want is not published yet. Here is what to install instead.
Gemma 4 12B: Google's New Local Multimodal Sweet Spot
A practical local AI guide to Google's new 12B Apache 2.0 model: unified multimodal input, 256K context and 16-32 GB hardware fit.
NVIDIA RTX Spark: The Local AI PC Apple Should Worry About
Blackwell RTX cores, Arm CPU cores, 128GB unified memory and the Windows on Arm problem: what RTX Spark really means for local LLMs and AI agents.
Ollama vs LM Studio in 2026: Which One Should You Use?
The practical local AI comparison: LM Studio wins for most desktop users, while Ollama remains the better backend for developers, agents, APIs, and automation.
Gemma 4 MTP Drafters: Multi-Token Prediction Explained
Google's MTP drafters for Gemma 4 use speculative decoding to predict multiple future tokens, verify them in parallel, and unlock up to 3× faster local inference.
Qwen 3.6-27B Deep Dive: Alibaba's Dense Flagship Reasoner
The biggest Qwen 3.6 — 27B dense parameters with hybrid thinking mode. Major quality leap over Qwen 3.5-27B in reasoning, coding & math. Fits on RTX 4090 & Mac Studio. Apache 2.0.
Gemma 4 Suite Deep Dive: E2B, E4B, 26B-A4B & 31B
Google's five-model Gemma 4 family spans E2B to 31B, with multimodal input, QAT checkpoints, model-specific context windows and practical local memory guidance.
GLM-5.2 Is Out: Can You Run This 744B Open Model Locally?
Z.ai's MIT open model brings 744B parameters, 40B active parameters and a 1M context. Here is the real Unsloth GGUF hardware story.
Qwen 3.6 Deep Dive: Alibaba's Hybrid-Thinking 6.7B
Alibaba's surprise launch — a 6.7B dense model with a unique hybrid thinking mode that switches between fast instruct and deep chain-of-thought on demand. Apache 2.0.
Best Local TTS Models in 2026: 58 Open Voice Models
Compare Dots TTS, Higgs Audio v2, MisoTTS, WavTTS, Orpheus, Kokoro and Piper with honest runtime, hardware and licensing guidance.
OpenClaw v2026.7.1: Install, Update & Run Locally
Foundations for the 2026.7.1 release: LM Studio, Ollama and configuration. For OpenClaw 2.0 and current LocalClaw compatibility, read the new release guide above.
How to Choose the Right Local LLM in 2026
Updated RAM and VRAM tiers from 8 GB laptops to 64 GB workstations, with current Qwen, Gemma, Ministral, Bonsai and Llama picks.
Qwen 3.5 Deep Dive: 35B-A3B, 27B, 122B-A10B, 397B-A17B
Complete guide to Qwen 3.5: MoE architecture explained, hardware requirements, benchmarks, and how to run the 35B-A3B on a Mac Studio 32GB.
Qwen3 8B vs Llama 3.3 70B: The Honest Local AI Comparison
A deployment reality check: Qwen3 has an official 8B checkpoint, while Meta's official Llama 3.3 release is 70B and targets much larger hardware.
Complete Guide: Q4, Q5, Q8 Quantization Explained
Which quantization to choose? Impact on quality, size, and performance. Everything you need to know about GGUF and K-quants.
Apple Silicon vs NVIDIA: Best Hardware for LLMs?
Current Mac Studio M4 Max and M3 Ultra versus NVIDIA RTX 4090 and 5090: memory capacity, CUDA speed, power and upgrade tradeoffs.
LM Studio Beginner Guide: From Zero to Your First LLM
Updated for LM Studio 0.4.x: installation, model discovery, load settings, context, MTP support and the local OpenAI-compatible API.
Best Local AI Models in 2026, Chosen by RAM
Practical current picks for 8, 16, 32 and 64 GB machines, plus an honest separation between desktop-ready models and server-scale open weights.
Start here
Turn the guide into a local AI setup
Pick the next step for your machine, your voice stack, or the native macOS app.