The Local LLM Glossary: Every Term, Flag, and Number in Plain English
Plain-English definitions for every term you hit in local LLM posts: prefill and decode, tokens per second, FP8 and NVFP4, Q4_K_M, KV cache, YaRN, Gated DeltaNet, speculative decoding, and every vLLM, llama.cpp, and Ollama flag worth knowing.
Running Qwen3.8-27B on DGX Spark
Qwen3.8-27B on DGX Spark with llama.cpp, Ollama, vLLM, and SGLang: the recipes, the tokens per second I measured, MTP speculative decoding, and the sharp edges I hit along the way.
I Ran an AI SRE Copilot on My Own Hardware. Here Is What It Actually Does.
Running NudgeBee v1.4.0 end to end - a self-hosted AIOps platform behind AI-SRE, AI-FinOps, AI-K8sOps, and agentic automation - on a Mac, a kiac cluster, and a DGX Spark.
Running Nemotron 3.5 Lightning on DGX Spark
NVIDIA's new Nemotron 3.5 Lightning on DGX Spark: how to run it with Ollama and vLLM, the tokens per second I measured, and how the two paths compare.
HAMi Dynamic MIG on RTX PRO 6000: A Live Kubernetes Test
Hands-on HAMi Dynamic MIG test on Kubernetes and RTX PRO 6000 Blackwell: setup commands, real allocations, mixed profiles, reclamation, and recovery.
Devin Outposts on Kubernetes: Why Your AI Agent Needs Your Cluster
Devin Outposts runs AI coding agent sessions as pods on your own Kubernetes cluster, with an open-source operator to manage the fleet.
How to Share GPUs in Kubernetes at Scale with HAMi (Software vGPU Slicing)
Share NVIDIA GPUs in Kubernetes with HAMi software vGPU slicing: memory and compute limits, Helm configuration, a verified PyTorch manifest, a real RTX PRO 6000 OOM test, and Prometheus monitoring.
Slicing GPUs in Kubernetes with NVIDIA Multi-Instance GPU (MIG)
GPU sharing in Kubernetes explained: time-slicing vs MPS vs MIG, every nvidia-smi command to enable and disable MIG on one GPU or eight, GPU Operator automation, pitfalls, and DCGM monitoring.
Day 5: Local LLM Inference Engines, Wrappers, and What to Pick
A beginner-friendly guide to local LLM inference, with the same Qwen model tested through Ollama, llama.cpp, Docker Model Runner, vLLM, SGLang, and TensorRT-LLM on NVIDIA DGX Spark.
Bonsai 27B on RTX PRO 6000 vs DGX Spark: what actually works
Real Bonsai 27B benchmarks on an RTX PRO 6000 and a DGX Spark, including the supported llama.cpp setup, ternary vs 1-bit results, and speculative decoding.
Introducing kiac: Real Kubernetes Nodes on Your Mac, Each Its Own Lightweight VM
kiac runs local Kubernetes on macOS where every node is its own lightweight VM via apple/container: kubeadm or k3s flavors, Cilium on a custom kernel, built-in LoadBalancer, Grafana, Gateway API, and clusters that survive reboots.
LLM Costs and Observability with agentgateway on Kubernetes (Part 2)
Part 2: scrape agentgateway with Prometheus, build a Grafana dashboard of token cost and per-tool usage, see blocked tool calls, and alert on spend.
Controlling MCP Tools with agentgateway on Kubernetes (Part 1)
Run AI agents behind agentgateway on Kubernetes: route their LLM and MCP tool calls through one proxy, keep secrets out of the agent, and block tools by policy.
Day 4: Quantization Demystified. BF16, FP8, NVFP4, MXFP4, INT4, GGUF, and Why It All Matters
A practical, beginner-friendly guide to BF16, FP8, NVFP4, MXFP4, INT4, and GGUF Q4_K_M on NVIDIA DGX Spark. Bytes per parameter, quality vs size, and which format to pick when.
Day 3: The DGX Spark Unpacked. GB10, Unified Memory, sm_121, and the One Reason This Hardware Exists
A practical teardown of NVIDIA DGX Spark's GB10 Grace Blackwell Superchip, unified memory, sm_121, NVFP4 tensor cores, memory reporting, and decode limits.