Local AI Without a GPU: What Actually Runs (October 2026)
Which open models run on CPU and RAM alone, how to size them, why mixture-of-experts helps, and what a machine with no discrete GPU cannot do.
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#ollama
Best Local LLM Runners (September 2026)
Ollama, LM Studio, Jan, llama.cpp and vLLM compared: licences, engines, OpenAI-compatible APIs, multi-user serving, and which to install first.
Local AI by VRAM: Which Models Fit Your GPU (September 2026)
Find your VRAM tier, then the current open-weight pick for chat, coding, vision, speech, translation or agents. Eighteen guides, one index.
6GB VRAM: What You Can Actually Run Locally (2026)
Local AI on a 6GB GPU: GTX 1660, RTX 2060, RTX 3050 and laptop cards. Real weight sizes for chat, coding, vision, speech, translation and RAG.
Qwen3.8-Max Goes Open Weight; 27B Targets 17GB
Alibaba announced 2.4T-parameter Qwen3.8-Max open weights and a 27B sibling that Unsloth says will run in 17GB of RAM or VRAM.
NadMesh Targets Exposed Ollama, ComfyUI, and n8n for Cloud Keys
A Go-based botnet is scanning exposed Ollama, ComfyUI, n8n, Open WebUI, Langflow, and Gradio instances for AWS keys and Kubernetes tokens, QiAnXin XLab says.
VKUE: Can a 34.7B Reasoner Run on a Laptop Without a GPU?
VIDRAFT_LAB posts Ourbox-35B-JGOS to Hugging Face: 20 tok/s on an 8GB laptop GPU, ~17 tok/s on a CPU-only server, 86.4% on GPQA Diamond.
AI Security Roundup: One Million Exposed Services and the Teenager Problem
Intruder scanned 2 million hosts and found 1 million exposed AI services with no authentication. Plus: teenagers are using ChatGPT to hack governments, and OpenAI launches Daybreak.
Open Source AI Wins: DeepSeek V4 Narrows the Gap, Apache 2.0 Becomes the Default, and Ollama Hits 52 Million Downloads
DeepSeek V4 Pro approaches frontier-level performance. Google, Mistral, and Alibaba ship under Apache 2.0. Ollama hits 52 million monthly downloads.
How to Build a Private RAG Chatbot With Open WebUI and Ollama
Chat with your own documents locally - no cloud, no subscriptions, no data leaving your machine. Step-by-step setup guide.
Self-host Vane (formerly Perplexica) to replace Perplexity with a private AI search engine
After the Perplexity class-action over leaked chats to Meta and Google, here's how to run a citation-grounded AI answer engine on your own hardware with Ollama and SearXNG.
Open-Weight LLM Showdown: GTC Pivots to Inference, DeepSeek V4 Still MIA
Jensen Huang bets on inference chips, Ollama adds multimodal support, and DeepSeek V4 remains the most anticipated release that hasn't happened yet.
Best Local AI Agent Models: Tool Use by GPU Tier (August 2026)
Which local models can actually use tools, call functions, and run multi-step workflows? Function-calling and TAU-bench picks from 8GB to 32GB VRAM.
Best Local Coding Models by VRAM Tier (August 2026)
Which open-weight coding model to run locally? HumanEval and SWE-bench picks from 8GB to 32GB GPUs. Qwen2.5-Coder, Qwen3.6, Devstral, KAT-Coder.
Best Local Models for Translation: Every VRAM Tier (August 2026)
TranslateGemma, NLLB-200, Aya Expanse and Qwen3.5 by VRAM tier, with the licence terms that decide whether you can ship what you run.
Best Local Chat Models by VRAM Tier (August 2026)
Head-to-head comparison of local chat and assistant models from 8GB to 32GB VRAM. Current picks: Qwen3.5, Gemma 4, GPT-OSS, Qwen3.6, and GLM-4.7-Flash.
Best Local Vision Models: Every GPU Tier (August 2026)
Local image analysis, OCR, and visual reasoning from 8GB to 32GB VRAM. Qwen3.5 replaces Qwen3-VL at most tiers, and 16GB stays unresolved.
llama.cpp Joins Hugging Face: What It Means for Local AI's Future
Georgi Gerganov's team is now at Hugging Face, unifying the model hub with the inference engine that powers Ollama, LM Studio, and the entire local AI ecosystem.
12GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on a 12GB GPU: chat, coding, vision, speech and agents for RTX 3060 12GB or RTX 4070. Current picks, per-quant weight sizes, honest limits.
16GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on a 16GB GPU: chat, coding, translation, speech and agents for RTX 4060 Ti, RTX 5060 or Arc A770, and why the vision tier stays unresolved.
24GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on a 24GB GPU: chat, coding, vision, speech and agents for RTX 3090 or RTX 4090. Current picks, per-quant weight sizes, and an open runtime bug.
32GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on a 32GB GPU: chat, coding, vision, speech and agents on an RTX 5090. Current picks, per-quant weight sizes, and what the headroom buys.
8GB VRAM: Every AI Task You Can Run Locally (August 2026)
Local AI on an 8GB GPU: chat, coding, vision, speech and agents for RTX 4060 or RTX 3070. Current picks, named quantisations, honest limits.
Apple M5 Max Makes 70B Parameter LLMs a Laptop Reality
The new MacBook Pro with M5 Max can run large language models entirely on-device, keeping your AI interactions private and offline