Recent Posts

• How to Run vLLM Natively on Windows 11 October 2026
  #production-inference#regulated-industry#vllm#windows#windows-deployment

  Practical guide to running vLLM directly on Windows systems without WSL or containers, enabling native local LLM inference on consumer Windows machines.

• Jeyzma: In-Browser LLM Inference with Go and TinyGo 11 October 2026
  #browser-inference#data-residency#llama-cpp#regulated-industry

  Jeyzma enables local LLM inference directly in web browsers using Go/TinyGo and llama.cpp integration, combining accessibility with privacy-preserving edge inference.

• Local LLM Inference at Scale with vLLM 11 October 2026
  #benchmarks#inference-optimization#inference-throughput#production-deployment#throughput-optimization#vllm

  Deep dive into using vLLM for high-throughput local LLM inference, covering optimization techniques and scaling strategies for self-hosted deployments.

• ML Drift: Google's Open-Source On-Device GPU Inference Engine 11 October 2026
  #google#gpu-optimization#inference-engine#performance-optimization

  Google releases ML Drift, a new open-source GPU inference engine optimized for on-device AI/ML workloads with focus on edge deployment scenarios.

• vLLM on Vera Rubin Posts 7.8x GB200 Throughput per Chip 11 October 2026
  #benchmarks#hardware-optimization#inference-throughput#nvidia#vllm

  vLLM achieves 7.8x throughput improvements on NVIDIA's GB200 hardware through Vera Rubin optimizations, demonstrating significant performance gains for local inference clusters.

• AWS, Upstage and Ollama Agree on Standardized LLM Inference API 10 October 2026
  #api-standardization#inference-optimization#ollama#openai#production-deployment

  Major cloud and open-source platforms have reached consensus on a unified API specification for LLM inference, creating interoperability standards that could reshape how local models integrate with broader ML ecosystems.

• ML Drift: Google's Open-Source On-Device GPU Inference Engine 10 October 2026
  #google#gpu-acceleration#gpu-inference#inference-engine#optimization#vllm

  Google has released ML Drift, a new open-source GPU inference engine specifically optimized for edge and on-device deployment scenarios. The framework focuses on GPU efficiency for local inference workloads.

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