Editorial desk
LM Studio Guide Editorial
The editorial desk that publishes LM Studio Guide. It is a byline for the site's editorial process, not a person, and this page carries no author biography because there is no individual author to describe.
How this desk works
- Articles are researched from primary sources: vendor and project documentation, published standards and specifications, release notes, advisories, and measurements published by the people who took them.
- Drafts are produced with AI assistance and then edited against those same sources before publication.
- Nothing published here claims hands-on lab testing, benchmarking, or first-hand measurement. Where a figure comes from a datasheet or someone else's test, the article names the source.
- Corrections go to [email protected] and are made on the affected page. Funding is set out on the disclosure page.
Posts (6)
- Comparisons
LM Studio vs Ollama for Local LLMs: How to Actually Choose
A practical comparison of LM Studio and Ollama for local LLMs: licensing limits, OpenAI API coverage, and the memory and context defaults.
- inference
How Much VRAM for a 7B Model? Quantization and Context
Size a 7B model using documented memory figures for BF16, INT8 and INT4. Account for KV cache, context length and LM Studio GPU offload.
- Model Formats
GGUF vs Safetensors: Differences and LM Studio Support
Compare GGUF and Safetensors for inference, training, quantization and LM Studio support, including when MLX safetensors models can load on Apple Silicon.
- Hardware
LM Studio System Requirements: RAM, VRAM, GPU
What LM Studio actually requires: 16 GB RAM, AVX2, 4 GB VRAM, macOS 14 on Apple Silicon, and how to size a machine for the model you want to run.
- Server & API
LM Studio on Unraid: Headless Server Setup
LM Studio has no official Unraid app. The three real options for headless GPU inference on a server, what each costs you, and which one to pick.
- Getting Started
GGUF Quantization Levels: Q4_K_M vs Q8_0 Explained
How GGUF quantization trades model quality for memory, what Q4_K_M costs you against Q8_0, and how to match a quant level to the memory you have.