The Calculator

Laguna S-2.1: 118B Model, 12GB Card. How CPU Offload Does It?

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How Does a 118B Model Run on a 12GB GPU? It doesn’t: not the way you’d assume. Nobody is holding a 118-billion-parameter model entirely in 12GB of VRAM; that’s not physically possible at any reasonable quantization. What’s actually happening is expert offloading: most of the model’s weights sit in ordinary system RAM, and only a … Read more

Rent a GPU for AI: Run High-End Models Before You Buy

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Can You Run High-End AI Without Buying a GPU? Yes — and it costs less than lunch. Running a 70-billion-parameter open-source model at home sounds like a five-figure hardware project, so most people never try. That belief is the single biggest reason capable developers stay on the sidelines of local AI. It is also wrong. … Read more

Local AI API Server: Setup, Real Limits, and the Fix

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How Do You Turn a Local LLM Into an API Server? Run it through Ollama or Jan, both of which expose an OpenAI-compatible endpoint on your own machine — http://localhost:11434/v1 for Ollama, http://localhost:1337/v1 for Jan. Point any tool built for the OpenAI SDK at that URL with any placeholder API key, and it behaves exactly … Read more

Kimi K3 VRAM Requirements: What 2.8T Actually Takes

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kimi k3 vram requirements

How Much VRAM Does Kimi K3 Need? The honest answer, as of July 16, 2026: no one can run Kimi K3 locally yet, and no one can compute its full memory footprint yet — but the official numbers already frame it. Moonshot’s launch post confirms a 2.8-trillion-parameter Mixture-of-Experts model shipping natively in MXFP4 — which … Read more

llama.cpp Performance Flags That Matter on Low VRAM

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llama.cpp performance flags

Which llama.cpp Flags Actually Improve Performance? Three, when VRAM is your binding constraint (flag syntax as of llama.cpp master, July 2026): -ngl (GPU layer offload) — the difference between GPU-speed and CPU-speed inference; -ctk/-ctv (KV cache quantization) — the highest-impact memory flag most people never set; and –spec-type ngram-* (n-gram speculative decoding) — the only … Read more

Run 405B on 8GB VRAM? No One Has Published the Speed

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Can You Really Run a 405B Model on 8 GB VRAM? Loading it: yes, demonstrably — AirLLM’s layer-streaming technique is real engineering. Running it at a published speed: nobody has shown that number. As of July 2026, no measured throughput figure — tokens per second — for Llama 3.1 405B via AirLLM exists in public: … Read more