Google Tensor G4
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Pixel 9 SoC. Google's mobile chip optimized for Gemini Nano + on-device transcription / summarization. NPU TOPS not publicly disclosed by Google; treat as on-par with mid-Snapdragon based on Gemini Nano benchmarks.
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Sub-scores sum to 231 / 1000. Headline = 231 × 0.70 (Estimated-confidence discount) = 162. 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 60 GB/s bandwidth — 4.8 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.
What it does well
The Google Tensor G4 is Google's custom Pixel phone SoC — co-designed with Samsung based on Exynos architecture and tuned for Google's first-party AI features (Gemini Nano on-device, Pixel Recorder transcription, Magic Editor, Best Take). 8 CPU cores + Mali-G715 GPU + Tensor Processing Unit (TPU) + 12 GB unified memory in Pixel 9 Pro. The chip ships in Pixel 9 / 9 Pro / 9 Pro XL at $799-$1,099 retail. Tensor G4's Google-tuned TPU is the canonical Android-side AI accelerator for first-party Google AI features — Gemini Nano runs natively, Pixel-specific features (Add Me, Pixel Studio) ship tuned to the silicon.
Where it breaks
- Raw silicon performance is below Snapdragon 8 Elite / 8 Gen 3. Tensor G4's CPU + GPU lag the contemporary Qualcomm flagships in benchmarks. Google prioritizes AI-feature integration over peak compute.
- Same iOS-equivalent sandbox limitations on Android. No proper LLM development workflow on the phone.
- TPU framework support is essentially Google-first-party. Third-party LLM frameworks targeting Tensor are thinner than Snapdragon's Qualcomm AI Hub ecosystem.
- Memory + bandwidth caps at phone tier. Sub-3B class on-device only.
- End-of-feature-support window. Google supports Pixel for 7 years; Tensor G4 is well-positioned for long-horizon support — Google's strongest pitch.
Ideal model range
- Sweet spot: Google's first-party Pixel AI features (Gemini Nano, Magic Editor, Best Take, Pixel Studio).
- Sweet spot: Pixel-form factor + AI as integrated feature, not the reason.
- Sweet spot: Long-horizon Android phone support (Google's 7-year update commitment).
- Bad fit: Anything beyond Google's first-party AI features.
Verdict
Buy Pixel 9 / 9 Pro / 9 Pro XL for the Pixel use case (camera, Google ecosystem, first-party AI features). Tensor G4 is the chip that makes Pixel-specific AI features work elegantly. For most readers, this verdict is informational reference about the silicon powering Pixel's AI integration.
Skip this if you want maximum raw phone performance (Snapdragon 8 Elite wins on benchmarks), you want Apple Intelligence (A18 Pro on iPhone 16 Pro), or you're shopping for AI development hardware (wrong tier).
How it compares
- vs Snapdragon 8 Elite → 8 Elite has higher raw CPU + GPU performance + 45 TOPS NPU. Tensor G4 has tighter Google-first-party AI integration. Pick by ecosystem priority.
- vs Snapdragon 8 Gen 3 → Generation match. Pick by phone OEM (Samsung/OnePlus vs Pixel).
- vs Apple A18 Pro → Different ecosystems entirely. Pick by Android vs iOS preference.
Overview
Pixel 9 SoC. Google's mobile chip optimized for Gemini Nano + on-device transcription / summarization. NPU TOPS not publicly disclosed by Google; treat as on-par with mid-Snapdragon based on Gemini Nano benchmarks.
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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: Pixel-only pathAndroid on-device AI stack — Phi-3.5 Mini / Llama 3.2 3B via MLC LLM or Qualcomm AI Hub
Tensor G4 ships in Pixel 9. Google's Gemini Nano runs natively. NPU TOPS aren't publicly disclosed — community benchmarks suggest mid-Snapdragon parity. Tensor's path is Pixel-locked.
Specs
| VRAM | 0 GB |
| System RAM (typical) | 12 GB |
| Power draw (peak) | 5 W |
| Released | 2024 |
| Backends |
Frequently asked
Does Google Tensor G4 support CUDA?
Where next?
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.