8 posts on SDAD Writes.
A high-end desktop is Rs 1.5-7 lakh behind a 230 V wall socket nobody controls. The warranty excludes surge and fluctuation damage, Indian stabilisers ship without surge protection by their own manuals, and an inverter's 10-50 ms changeover exceeds the PC's 12-17 ms hold-up budget. This is the full technical and financial case for all three layers.
Two developments are breaking NVIDIA's CUDA monopoly: the Vulkan compute backend for llama.cpp (cross-vendor LLM inference on any GPU) and the Mojo programming language (a CUDA alternative that compiles to any accelerator).
Real Qwen3.8-27B numbers on the DGX Spark GB10: the memory wall caps single-stream decode at 11-12 tok/s, and speculative decoding is the only way out. SGLang with DSpark hits 34 tok/s, veloGB10 reaches about 40 tok/s, and NVFP4 keeps quality within noise of FP8.
VRAM is everything for local AI agents: the 4-bit cheat sheet runs 7B at about 5GB, 14B at 10GB, 30B at 20GB, and 70B at 40GB. Three builds cover it, from a $1,200-1,500 RTX 4060 Ti 16GB starter to the used 24GB-card sweet spot that runs 32B models at near-cloud quality for daily work.
Claude Code ranked the best local AI model for each VRAM tier from 4GB to 384GB - Nanbeige 3B at 4GB to Motif-3 314B at 384GB. Fact-checked July 2026: all five picks are real, available, and the 5.9GB Bonsai 27B even runs on an iPhone.
The memory wall ends here: NVIDIA's DGX Station pairs 252GB of HBM3e at 7.1TB/s with 496GB of LPDDR5X into one 748GB coherent pool on GB300 Grace Blackwell Ultra, adds NVFP4 quantization and 800Gbps ConnectX-8 networking (two boxes pool about 1.5TB), at roughly $94,930.
AMD's $1500 Strix Halo runs the same 120B model as Nvidia's $4700 DGX Spark, only 13% slower. But DGX Spark wins prefill by 3x and compute by 13x. Full benchmarks, India pricing, and a hands-on check on 2x DGX Spark GB10 with a 30B Q4 model.
Every AI system runs on one of five chip types — CPU, GPU, TPU, LPU, or NPU. Each makes a different tradeoff between flexibility and speed. This guide explains all five in plain English, with enough depth to actually help you decide which one matters for your work.
