Andrew Dyuzhov

What does LLM temperature do? Compare 900 model responses, see examples at 0, 0.7 and 1.5, and learn how to choose settings and adjust them in Atomic Chat.

GPT-6 Astra benchmarks and open-weight alternatives. Connect your ChatGPT subscription in Atomic Chat, or run Qwen and Laguna on your own hardware.

Run Qwen3.8 Flash Next uncensored locally from 80 GB up. Compare the community abliterations, pick the GGUF that fits your memory, then run it in Atomic Chat.

Qwen3.8 Flash Next runs from 64 GB of RAM up with its n-gram table on SSD. Pick the Atomic Dynamic GGUF that fits, then run it with Atomic Chat or llama.cpp.

Ornith 1.5 uncensored runs from 6 GB up. Compare the community abliterations of the 9B and the 35B, then run one locally with Atomic Chat or llama.cpp.

Run Qwen 3.8 27B uncensored locally from 12 GB with a low-bit GGUF. Use Q4_K_M on a 24 GB GPU or 4-bit MLX on a 32 GB Mac.

Ornith 1.5 35B runs from a 12 GB GPU up with expert offload. Pick the Atomic Dynamic GGUF that fits, then run it locally with Atomic Chat or llama.cpp.

Ornith 1.5 9B runs from 6 GB up, 4 GB text-only. Pick the Atomic Dynamic GGUF that fits your hardware, then run it locally with Atomic Chat or llama.cpp.

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.

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.

Compare 10 uncensored LLMs to run locally in 2026, including Ollama builds and abliterated models, with setup advice and benchmarks.

Learn about GGUF, the file format for local AI models: how it works, what Q4_K_M means, and how to choose a quantization.

Learn how speculative decoding accelerates LLM generation by drafting and verifying tokens, and how Atomic Chat uses it.

NVFP4 is a 4-bit NVIDIA format for smaller LLMs and faster inference on Blackwell GPUs. Learn how its block scaling and quantization work.

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.

We benchmarked Ollama and llama.cpp with the same model and hardware. Compare speed, setup, interfaces, and see which local LLM runner fits you.

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.

Is Ollama safe? Review local LLM security risks and learn how to check and harden your Ollama setup.

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.