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docs/app/stacks/ai-first/page.mdx
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title: "The AI-First Stack"
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description: "Own your AI. Run LLMs, image generation, and code assistants locally with zero API keys, zero usage limits, and zero data leaving your machine."
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---
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# 🤖 The AI-First Stack
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**Own your AI.** Run powerful AI locally. No API keys, no usage limits, no data leaving your machine.
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| What | Tool | Replaces |
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|---|---|---|
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| LLM Inference | [Llama](/deploy/llama) | ChatGPT ($20/mo) |
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| Coding Model | [DeepSeek](/deploy/deepseek) | GitHub Copilot ($10/mo) |
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| Image Generation | [Stable Diffusion](/deploy/stable-diffusion) | Midjourney ($10/mo) |
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| IDE Assistant | [Continue.dev](/deploy/continue-dev) | Copilot extension ($10/mo) |
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| Code Autocomplete | [Tabby](/deploy/tabby) | Tabnine ($12/mo) |
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**Total saved: ~$69/mo** (nice)
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## Hardware Requirements
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Running AI locally requires GPU horsepower. Here's what you need:
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| Model Type | Minimum VRAM | Recommended GPU |
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|---|---|---|
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| Small LLMs (7B params) | 6 GB | RTX 3060, RTX 4060 |
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| Large LLMs (70B params) | 48 GB | 2× RTX 3090, A6000 |
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| Image Generation (SDXL) | 8 GB | RTX 3070+ |
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| Code Models (DeepSeek) | 8 GB | RTX 4060+ |
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> 🔥 **Pro Tip:** Start with Ollama + Llama 3. It runs well on an 8GB GPU and gives you a local ChatGPT replacement in under 5 minutes.
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## Deploy Guides
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→ [Deploy Ollama (LLM Runner)](/deploy/ollama)
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→ [Deploy Stable Diffusion](/deploy/stable-diffusion)
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→ [Deploy Tabby (Code AI)](/deploy/tabby)
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→ [Deploy Continue.dev](/deploy/continue-dev)
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