#openvino

In April I wrote that your Intel laptop can run LLMs. That post was about 8B models — good little...

Run YOLO Vision Models: Deploy Ultralytics YOLO on a Raspberry Pi 4 or 5 with Intel OpenVINO for real edge computer vision, no cloud GPU or workstation needed.

How a subtle race condition in async inference queues returned syntactically valid embeddings for the wrong inputs — and how to catch it with a cosine contamination test.

OpenVINO 2026.0 brings full NPU LLM support, a Unified Runtime Scheduler, and INT4 quantization. Install guide, Python quickstart, and model matrix.

In Q3 2024, 72% of production AI inference pipelines using OpenVINO 2024.3.0 and Mistral 2 7B exposed...

In Q3 2024, 68% of LLM deployment teams reported overspending on inference infrastructure by ≥40% due...

In Q3 2024, our inference pipeline’s p99 latency hit 2.1 seconds for 7B parameter LLMs quantized to...

RAG pipelines built with OpenVINO 2024.3 and ONNX Runtime 1.18 deliver 42% lower p99 latency and 37%...

In 2024, we ran 10,000 inference iterations across 12 model families and found OpenVINO outperforms...

TensorRT Deep Dive OpenVINO: Avoid Deployment for Developers For developers working on...

In 2024, we benchmarked 127 production-grade CV and LLM models across 4 GPU architectures and 2 Intel...

Update august 2026: I have succeded in enabling SSD offload and more with latest OpenVINO 2026.3 -...