Sector-specific AI playbooks across 10 industries we know cold.
View all industries →APAC ML teams running unoptimized PyTorch inference in production are leaving 2-10× performance improvement on the table. This guide explains how ONNX Runtime, OpenVINO, and llama.cpp address cross-platform optimization, Intel CPU inference, and on-device LLM serving — with APAC data sovereignty considerations and hardware-specific deployment guidance.
Beyond this insight
If this article matches your stage of thinking, the underlying capabilities ship across all six pillars, ten verticals, and nine Asian markets.
APAC teams fine-tuning large language models face three recurring bottlenecks: GPU memory, training speed, and multi-GPU coordination. DeepSpeed, PEFT, and Unsloth address each layer — this guide explains how to combine them into a cost-efficient APAC fine-tuning stack with practical code examples and cost scenarios.
BlogThree GPU cloud models — reserved dedicated compute, distributed marketplace, and serverless inference — each optimise for different APAC AI workload patterns. This guide maps Lambda Labs, Vast.ai, and Inferless to training, research, and inference use cases with APAC cost scenarios and a decision matrix.
BlogA practitioner guide for APAC AI engineering teams selecting execution infrastructure for AI agent code sandboxes, ML model inference, and serverless GPU compute in 2026 — covering E2B as secure cloud sandboxes for running LLM-generated Python code in isolated environments, enabling APAC AI data analyst and coding agent applications to execute arbitrary code safely without production infrastructure risk; Baseten as a managed ML model inference platform that converts PyTorch and HuggingFace models to auto-scaling GPU APIs via its Truss packaging framework, with TensorRT optimization and scale-to-zero for APAC variable traffic workloads; and Cerebrium as a serverless GPU cloud with sub-second cold starts on H100/A100 hardware, charging per GPU-second for APAC teams with bursty inference or training workloads who need flexible access to high-end GPU without committed instance costs.
We use these frameworks daily in client engagements. Let's see what they look like for your stage and market.
