--- title: My Complete Local AI Setup - $7000+ | daily.dev description: A detailed walkthrough of a $7,000 local AI hardware and software setup built around an Nvidia GB10-based Dell Pro Max with 128GB unified memory. Covers... canonical: https://daily.dev/posts/my-complete-local-ai-setup---7000--zplsztamd twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: My Complete Local AI Setup - $7000+ | daily.dev og:description: A detailed walkthrough of a $7,000 local AI hardware and software setup built around an Nvidia GB10-based Dell Pro Max with 128GB unified memory. Covers... og:url: https://daily.dev/posts/my-complete-local-ai-setup---7000--zplsztamd og:image: https://api.daily.dev/og/posts/zPLSZTamd.png og:image:alt: My Complete Local AI Setup - $7000+ og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # My Complete Local AI Setup - $7000+ **[Tech With Tim](https://daily.dev/sources/TechWithTim)** · 18 min read · 1 upvotes · 0 comments ## Summary A detailed walkthrough of a $7,000 local AI hardware and software setup built around an Nvidia GB10-based Dell Pro Max with 128GB unified memory. Covers running mixture-of-experts models like Qwen3.6 and Nvidia Nemotron variants via Llama.cpp/Llama Swap, Ollama, and vLLM, plus optimizations like speculative decoding, quantized KV cache, flash attention, and Tailscale networking to hit 70-80+ tokens/second on coding models. Includes measured token-per-second benchmarks across several models and practical tips for maximizing throughput and context window size on local hardware. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What does the A3B naming mean in mixture-of-experts models like Qwen3.6? A3B indicates a mixture-of-experts model has 3 billion active parameters per token, even though the total parameter count is much larger. This lets the model run at roughly the inference speed of a small model while retaining the intelligence benefits of a much larger one, which is why these MoE models are favored for fast local inference on GPUs with limited compute. _Developers picking a local model architecture can compare MoE tradeoffs like this on daily.dev before committing hardware._ ### How much does speculative decoding improve local LLM inference speed? Speculative decoding roughly doubled token-per-second speed in real testing, taking a Nemotron Super 120B model from about 16.6 tokens per second up to 27.2 tokens per second (a 64% increase) after enabling MTP along with flash attention and quantized KV cache, measured at a 17,000 token context length. _Anyone tuning local inference throughput can track optimization techniques like this on daily.dev._ ### Why would you choose a GB10-based machine with 128GB unified memory over a consumer GPU like an RTX 4090 for local AI? A 128GB unified memory machine like the Nvidia GB10-based Dell Pro Max lets you load much larger models that simply don't fit in a 24GB RTX 4090's VRAM, even though the 4090 has faster raw inference speed. The GB10 box also runs headless over SSH/Tailscale without hogging a monitor GPU, trading some memory speed for far greater model capacity and multi-model flexibility. _Developers weighing local hardware options for AI workloads can dig into comparisons like this on daily.dev._ --- Tags: [#data-science](https://daily.dev/tags/data-science), [#nvidia](https://daily.dev/tags/nvidia), [#vllm](https://daily.dev/tags/vllm), [#llama-cpp](https://daily.dev/tags/llama-cpp) [View this post on daily.dev](https://daily.dev/posts/my-complete-local-ai-setup---7000--zplsztamd) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"My Complete Local AI Setup - $7000+","url":"https://daily.dev/posts/my-complete-local-ai-setup---7000--zplsztamd","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/my-complete-local-ai-setup---7000--zplsztamd"},"datePublished":"2026-09-02T14:15:40.547Z","dateModified":"2026-09-02T14:16:03.280Z","description":"A detailed walkthrough of a $7,000 local AI hardware and software setup built around an Nvidia GB10-based Dell Pro Max with 128GB unified memory. 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