Tagged "hardware-requirements"
8 articles tagged hardware-requirements, 13 May 2026 to 18 October 2026. Newest first.
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Ollama GPU Requirements Guide: VRAM, RAM, and Supported GPUs
Comprehensive reference guide covering GPU memory requirements, RAM specifications, and supported hardware for running Ollama locally, helping practitioners make informed deployment decisions.
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How to Choose the Best Local LLM Based on MacBook RAM Size
A practical guide matching LLM model sizes to MacBook specifications, providing evidence-based recommendations for running local models across the full range of Apple Silicon configurations.
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Ollama GPU requirements: VRAM, RAM, and supported GPUs
Hostinger's comprehensive breakdown of hardware requirements for running Ollama, covering VRAM needs, system RAM, and GPU compatibility across different model sizes and architectures.
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Picking a Local LLM for Coding: What Fits on Your Machine and What Still Needs an API
Practical guidance on selecting appropriate local LLM models for coding tasks based on hardware constraints, helping developers understand model-to-machine matching.
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Google Chrome Reveals Storage Requirements for Integrated Local AI Models
Google discloses how much free disk space Chrome requires to install and run local AI models, indicating the browser is moving toward on-device model deployment for inference.
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How to Run LLM Locally Without Falling for the Hype
Practical guide addressing common misconceptions and providing actionable steps for deploying large language models on local hardware. Emphasises realistic expectations and cost-benefit analysis.
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Google Limits Gemini Intelligence to New Flagships—Hardware Requirements for Local Deployment
Google has unveiled Gemini Intelligence capabilities restricted to flagship devices, with extreme hardware requirements that limit deployment scope. This underscores the ongoing challenge of fitting capable AI models into accessible, consumer-level hardware.
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I Stopped Paying for ChatGPT and Switched to a Local LLM That Runs on My Laptop
A user shares their experience transitioning from cloud-based AI services to a locally-hosted LLM on consumer hardware, highlighting cost savings and practical considerations for making the switch.