Best Local LLMs You Can Run on a Single 24GB GPU in 2026: Qwen, Gemma, Mistral, DeepSeek Compared
A guide compares six open-weight models that fit a single 24GB GPU, including Qwen3.6, Gemma 4, and Mistral Small.
- Qwen3.6, Gemma 4, and Mistral Small are top local LLMs for a 24GB GPU in 2026.
- Each model has its strengths and weaknesses, and the guide helps developers and researchers choose the right one.
- The models compared in this guide are all open-weight and designed to fit a single 24GB GPU.
A single 24GB GPU is the practical floor for serious local inference. This guide compares six open-weight models that fit one card at Q4_K_M, including Qwen3.6, Gemma 4, Mistral Small, gpt-oss-20b, and DeepSeek-R1-Distill. Each entry lists VRAM fit, licensing, and the job it does best. This comparison is essential for developers and researchers looking to deploy local LLMs on a single 24GB GPU in 2026.
The models compared in this guide are all open-weight, meaning they can be used for free, and are designed to fit a single 24GB GPU. This makes them ideal for developers and researchers who want to deploy local LLMs without breaking the bank.
The guide covers the key features of each model, including VRAM fit, licensing, and the job it does best. This information is essential for developers and researchers who want to choose the right model for their needs.
This guide helps developers choose the right local LLM for their needs.
This guide is essential for businesses looking to deploy local LLMs on a single 24GB GPU.
This guide provides a comprehensive comparison of top local LLMs for a 24GB GPU in 2026.
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