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The best local LLMs for 8GB VRAM and 8GB RAM in 2026: Qwen 3.5 9B and 4B, GLM-4.6V-Flash, DeepSeek-R1, Phi-4 Mini, Gemma 3 4B, and SmolLM3 — with sizes and quants.

Qwen 3.8 27B runs from 12 GB up. Pick the Atomic Dynamic GGUF that fits your hardware, then run it locally with Atomic Chat or llama.cpp. Benchmarks included.

Step-by-step guide to running a self-hosted LLM with Atomic Chat: hardware requirements, the best open models of 2026, and how to expose a local API.

What a KV cache is, why it grows with context length, and how much RAM or VRAM it needs — with an interactive KV cache calculator and TurboQuant compression data.

DeepSeek V4 Flash needs 70–162 GB on disk. Pick the Atomic Dynamic GGUF that fits your memory, then run it locally with Atomic Chat or llama.cpp.

Run Ling 3.0 Flash on your own machine: hardware requirements, Atomic Dynamic GGUF builds, and setup with Atomic Chat or the TurboQuant llama.cpp build.

Run GLM locally with Atomic Chat: pick the right GLM-4.7-Flash or GLM-5.2 build for your hardware, download a GGUF, and chat entirely offline.

Learn how to run Qwen locally: pick the right model for your hardware, download the best GGUF quantization, and chat offline using Atomic Chat.

Run Kimi K3 locally: hardware requirements, Atomic Chat setup, renting 8x B300 GPUs on Vast, real costs, and the errors I hit along the way.

Run Google’s Gemma 4 models on your own machine. Pick the right size for your RAM or VRAM, choose a GGUF quantization, and start chatting locally.

Run Nous Research’s Hermes Agent locally, powered by a local model served through Atomic Chat — no cloud account and no API key. A step-by-step guide.

How to run AI agents locally for free: the best local models for agentic coding, hardware requirements, and a step-by-step setup guide with Atomic Chat.

Run the OpenClaw AI agent locally for free by powering it with a local model served from Atomic Chat — no cloud, no per-token bills, fully private.

The best uncensored LLMs to run locally in 2026 — 10 models ranked, from the most-downloaded Ollama builds to abliterated long-context beasts. Setup, benchmarks, picks.

GGUF is the file format local AI models ship in. Here's what it is, what Q4_K_M means, and which quantization to actually download.

Speculative decoding speeds up LLM generation with no quality loss by drafting tokens ahead and verifying them in one pass. How it works, and how Atomic Chat uses it.

NVFP4 is NVIDIA's 4-bit format that shrinks LLMs to a quarter of their size and runs them faster on Blackwell GPUs, with under 1% accuracy loss.

Learn how to run an LLM locally on your computer or Mac — pick a model for your hardware, understand quantization, and set it up in a few clicks, for free.

Run gpt-oss locally on your own machine. A step-by-step guide to gpt-oss-20b and gpt-oss-120b — the hardware you need and the fastest setup, fully offline.

Ollama vs llama.cpp explained: llama.cpp is the C/C++ engine, Ollama is the wrapper on top. How they compare on speed, setup, and the best alternatives.

How to run DeepSeek R1 locally and offline — which distilled sizes fit your hardware, and step-by-step setup with Atomic Chat or Ollama.

The 10 best local LLM apps in 2026, compared on interface, platform reach, openness, and tool support — and which one to start with.

See how the best local LLMs for coding compare across benchmarks, which model we recommend for different use cases, and the key takeaways from our testing.

GGUF vs MLX on Mac: why tok/s is a misleading metric, how prefill determines real speed, and benchmarks across 5 runtimes on M1 Max and M5 Max.

Cloud AI leaks data and goes down. Offline AI runs local LLMs on your own machine. A practical guide to hardware, models, and setup that works.

Bleeding Llama leaked data from 300,000 Ollama servers. Is Ollama safe? Audit and secure your local LLM setup in 15 minutes

6 local LLMs that fit a 16GB Mac in 2026, with token speeds from public benchmarks, RAM usage, and a short guide to running them.