Qualcomm Snapdragon 8 Elite
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Late-2024 Android flagship SoC. Oryon CPU + Hexagon NPU. 8B-class models become viable on-device with adequate quantization.
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Sub-scores sum to 311 / 1000. Headline = 311 × 0.70 (Estimated-confidence discount) = 218. This is an algorithmic performance-tier score — distinct from, and often lower than, the editorial “Our verdict” below, which weighs value and real-world fit (especially for hardware we haven’t measured yet). How scoring works →
Extrapolated from 90 GB/s bandwidth — 7.2 tok/s estimated. No measured benchmarks yet.
Plain-English: Doesn't fit modern chat models usefully.
Verdicts extrapolated from catalog VRAM + bandwidth + ecosystem flags. Hover any chip for the rationale. Want measured numbers? Submit your own run with runlocalai-bench --submit.
Our verdict
What it does well
The Qualcomm Snapdragon 8 Elite is the 2025 flagship Android phone SoC and the most credible Android-side AI chip — 8 Oryon CPU cores + Adreno 830 GPU + dedicated Hexagon NPU (Qualcomm publishes no TOPS figure for it). Ships in flagship Android phones from Samsung Galaxy S25 Ultra, OnePlus 13, Xiaomi 15 Pro, ASUS ROG Phone 9. For on-device AI features (Google Gemini Nano, Samsung Galaxy AI, OEM-specific AI features), Snapdragon 8 Elite is the canonical Android-side AI accelerator. The chip runs sub-3B class Gemini Nano-tier models comfortably for tasks like summarization, translation, smart reply, on-device image generation. For LLM-curious developers, Qualcomm's AI Hub + ONNX Runtime + llama.cpp Vulkan paths run on the Adreno GPU with reasonable throughput.
Where it breaks
- Phone form factor limits all serious AI development. No Terminal-grade access, no proper Python development, sandboxed runtime. You consume AI features in apps, not develop against them on the device.
- Memory ceiling at up to 24 GB of system RAM, shared with the OS and apps.
- No CUDA, no ROCm, no Metal. Adreno (Vulkan, OpenCL) + Hexagon NPU only.
- Day-zero new model architecture support arrives last on phone SoCs. Mobile silicon is the slowest tier for LLM framework support.
- OEM software fragmentation. Different phones expose different AI APIs (Samsung Galaxy AI vs OEM custom vs Google AICore).
Ideal model range
- Sweet spot: Sub-3B class on-device inference (Gemini Nano, Apple Intelligence-equivalent on Android, smaller transformer-based features).
- Sweet spot: Real-time on-device features (live translation, voice transcription, smart reply, summarization).
- Sweet spot: Phone-form-factor creator AI (image generation, photo editing AI, voice synthesis).
- Bad fit: 7B+ FP16 anything, fine-tuning, AI development workflows, CUDA-required.
Verdict
Buy a phone with Snapdragon 8 Elite for the phone use cases (camera, gaming, productivity) — the AI is a feature, not the reason. For on-device AI features (summarization, translation, image generation), 8 Elite is genuinely capable. For most readers, this verdict is informational reference about the silicon powering 2025-2026 flagship Android AI features.
Skip this if you're shopping for AI development hardware — phones aren't the right tier. Pick a Mac mini M4, discrete-GPU laptop, or workstation for serious local AI.
How it compares
- vs Apple A18 Pro → A18 Pro powers iPhone 16 Pro. Apple Intelligence vs Google Gemini Nano + Samsung Galaxy AI — different ecosystem, similar capability tier.
- vs Snapdragon 8 Gen 3 → Prior-gen, and Qualcomm describes the 8 Elite NPU as faster. 8 Elite is the strict generational upgrade.
- vs Google Tensor G4 → Google's custom SoC in Pixel phones with deep Gemini Nano integration. Tensor G4's NPU is lower-throughput but tightly integrated with Google's first-party AI stack.
- vs Snapdragon X Elite (laptop) → SDX Elite is the laptop variant with more cores + memory + thermal envelope. 8 Elite is phone-form factor — different scale entirely.
Overview
Late-2024 Android flagship SoC. Oryon CPU + Hexagon NPU. 8B-class models become viable on-device with adequate quantization.
Prices quoted in the review text are estimates from when it was written. Check the current price before you buy.
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Featured in this stack
The L3 execution stacks that pick this hardware as a recommended component, with the one-line note explaining the role it plays in each.
- Stack · L3·Homelab tier·Role: Target SoC (flagship 2024-2025)Android on-device AI stack — Phi-3.5 Mini / Llama 3.2 3B via MLC LLM or Qualcomm AI Hub
Snapdragon 8 Elite Hexagon NPU at ~80 TOPS INT8 + Adreno GPU. The 16GB RAM tier enables comfortable 3-4B model headroom. Pair with Qualcomm AI Hub for production NPU-first deployment.
Specs
| VRAM | 0 GB |
| System RAM (typical) | 16 GB |
| Power draw (peak) | 5 W |
| Released | 2024 |
| Backends | Vulkan |
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Frequently asked
Does Qualcomm Snapdragon 8 Elite support CUDA?
Where next?
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.