llama.cpp VRAM Requirements: Complete 2026 Guide to GPU Memory for Local LLMs

A benchmark-driven guide to llama.cpp VRAM requirements. Understand the exact memory needs for different models with massive 32K and 64K context lengths, backed by real-world data for smooth local LLM setups.

Updated March 11, 2026Read more

Ollama VRAM Requirements: Complete 2026 Guide to GPU Memory for Local LLMs

A benchmark driven guide to Ollama VRAM requirements. Understand the exact memory needs for different models backed by real world performance data for smooth local LLM setups.

Updated February 3, 2026Read more

LM Studio VRAM Requirements for Local LLMs

Running large language models (LLMs) locally has become more accessible with user-friendly tools like LM Studio, but VRAM (video RAM) remains the primary hardware bottleneck for anyone aiming for smooth, fast AI inference. This guide details exactly how much VRAM you need for running models in LM Studio, how configuration and quantization affect memory requirements, and what to do if your GPU isn't enough.

Published October 4, 2025Read more

Qwen3-Next-80B-A3B: The Future of Efficient Local LLMs

Revolutionary 80-billion parameter model with only 3 billion activated per inference achieves 10x cheaper training and 10x faster inference through ultra-sparse Mixture-of-Experts architecture and hybrid attention mechanisms.

Published September 13, 2025Read more

The Best GPUs for Local LLM Inference in 2025

Comprehensive analysis of the best GPUs for local LLM inference in 2025, featuring RTX 5090 performance benchmarks, MoE model requirements, and budget recommendations from Intel Arc B580 to enterprise H100 solutions.

Published August 30, 2025Read more