Home / Services / edge-ai-inference / Qualcomm AI Engine — Mobile & IoT Edge AI Processing edge-ai-inference Qualcomm AI Engine — Mobile & IoT Edge AI Processing Qualcomm AI Engine, integrated into Snapdragon mobile and IoT platforms, brings dedicated AI acceleration to over 1 billion devices. Its Hexagon Neural Processing Unit (NPU) handles on-device LLM inference (up to 7B parameters), real-time translation, voice assistants, and computational photography without cloud round-trips.
Features ✦ Hexagon NPU supports 48 TOPS INT8 inference performance ✦ On-device LLM inference: Llama 3 7B at 15+ tokens/second ✦ Hybrid AI: automatic split between on-device and cloud inference ✦ Qualcomm AI Engine Direct — single API for GPU, CPU, NPU acceleration ✦ Supports ONNX, TensorFlow Lite, PyTorch Mobile runtimes ✦ Always-on voice, vision, and sensor processing at <5mW Pricing basic Integrated into Snapdragon SoCs
pro Developer access via Qualcomm Innovation Center
enterprise Custom NPU firmware licensing available
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Benefits ✓ User voice data never leaves the device — privacy by architecture
✓ Offline AI works in airplane mode, underground, remote areas
✓ Real-time multilingual translation for 40+ languages on Snapdragon
✓ Smartphone camera computational photography at professional quality
✓ Battery-efficient: 10-hour continuous AI workload vs 2 hours on GPU
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Deployment Roadmap AI-Inferred • 5 phases Estimated timeline for Qualcomm AI Engine — Mobile & IoT Edge AI Processing — adapt to your team size and complexity.
1. Requirements & Design Week 1–2 ✓ Stakeholder requirements workshop ✓ Solution architecture + diagram review ✓ Estimate effort + resource plan ✓ Success metrics + SLAs agreed
2. Foundation Build Week 3–5 ✓ Core infrastructure + data pipeline ✓ Access control + security hardening ✓ Integration with existing systems ✓ Automated test suite setup
3. Test & Validate Week 6–7 ✓ User acceptance testing ✓ Performance + load testing ✓ Security review + sign-off ✓ Change management communication
4. Deployment & Stabilisation Week 8 ✓ Blue-green or canary deployment ✓ Hypercare period (3–5 days) ✓ Post-launch performance review ✓ Documentation + knowledge transfer
5. Optimise & Evolve Ongoing ✓ Usage + cost analytics ✓ Feature iteration backlog ✓ Vendor relationship + renewals ✓ Quarterly business review Related Services Other edge-ai-inference services you may be interested in
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