AI Infrastructure
VPS or GPU Hosting? Choose the Right Engine for Your Workload
A practical guide to choosing between VPS and GPU hosting based on your actual project needs, not marketing buzzwords.
Host Stinger
ReadBuilding and scaling AI systems — inference, vector databases, and orchestration
5 posts in this category
A practical guide to choosing between VPS and GPU hosting based on your actual project needs, not marketing buzzwords.
An in-depth technical analysis of the late-2026 breakthroughs in LLM serving infrastructure. Analyze the mechanics of Multi-head Latent Attention (MLA), the vLLM V1 engine rewrite vs. SGLang, Disaggregated Prefill/Decode, and EAGLE-3 speculative decoding.
An exhaustive technical exploration of late-2026 breakthroughs in LLM serving infrastructure. Analyze block-scaled native FP4 quantization on Blackwell, master the mathematics of weight-absorbed Multi-head Latent Attention (MLA), and deploy a production-grade disaggregated prefill-decode cluster with SGLang and vLLM.
Deconstruct the physical infrastructure shift of inference-time compute. Learn how to scale the serving stack for reasoning models like DeepSeek-R1 and OpenAI o1, implement prefill-decode disaggregation, configure SGLang and vLLM parsers, and overcome critical production roadblocks such as JIT compilation deadlocks and MoE network saturation.
An in-depth technical analysis of the late-2026 breakthroughs in LLM serving infrastructure. Contrast SGLang and vLLM V1, master the mathematics of Multi-head Latent Attention (MLA) cache compression, configure EAGLE-3 speculative decoding, and deploy an optimized serving cluster with a step-by-step walkthrough.