How to Read LLM Benchmarks Before You Pick a Local Model: A Buyer’s Guide to Leaderboards
How to read LLM benchmarks: what MMLU, GPQA, Arena votes and llama-bench measure, leaderboard traps, and a 20-prompt test you can run yourself.
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Gemma Local Deployment Guide: Run Gemma 4 and Gemma 3 with Ollama, Sized by VRAM
Gemma local deployment with Ollama: compare Gemma 4 e2b, e4b, 12b, 26b and 31b sizes and context, pick one by VRAM, and set thinking mode, sampling, and fixes.
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How to Run DeepSeek Locally: Distilled vs Full Model, Picked by VRAM
Run DeepSeek locally the right way: R1 distills vs the full model vs V4, which Ollama tag fits 8GB to 48GB of VRAM, and four commands to get started.
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Running an LLM on 24GB VRAM: What Can an RTX 3090 / 4090 Run?
Which LLMs fit on 24GB VRAM? 27B–32B dense and 30B MoE models with memory estimates, long-context headroom, 3090 vs 4090, and why 70B doesn’t fit.
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Run an LLM on 8GB VRAM: What Can an 8GB GPU Run? Model Picks
Run an LLM on 8GB VRAM: Ollama picks for chat, reasoning, coding and vision with file sizes, context settings, 8GB card comparison and upgrade advice.
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Best Local LLM in 2026: Pick by VRAM and Task, Not by Leaderboard
Best local LLM for your hardware: picks by 8GB, 12GB, 24GB and 32GB VRAM and by task, covering Qwen, Gemma and gpt-oss, with file sizes and VRAM estimates.
