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Tensor G3 vs A16 Bionic: A16 Leads in Geekbench 6

A16 Bionic leads Tensor G3 in the paired Geekbench 6 CPU aggregates, but benchmark versions, phones, and AI frameworks matter when interpreting the comparison.
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Apple’s A16 Bionic scores higher than Google’s Tensor G3 in the paired Geekbench 6 comparison available here. NanoReview reports 2,631 versus 1,722 in single-core and 6,602 versus 4,458 in multi-core. Those are database aggregates from submitted tests, not a controlled head-to-head phone test, and they do not settle every question about gaming, AI, battery life, or sustained speed.

What devices are being compared?

Tensor G3 is the processor Google lists for the Pixel 8 family. The comparison’s A16 Bionic results are associated with the iPhone 14 Pro; they should not be mistaken for results from the base iPhone 14, which uses a different chip. The phones are useful context, but device characteristics such as memory, cooling, battery, and software are not properties of the processor alone.

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Google lists 8 GB of LPDDR5X memory for Pixel 8. That is the phone’s RAM specification, not a Tensor G3 specification. Google also says Pixel 8 and Pixel 8 Pro receive seven years of updates from their first US Google Store availability. These details may matter when choosing a phone, but they do not change the benchmark scores below. Google’s Pixel hardware specifications

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Geekbench 6: A16 leads in both CPU tests

NanoReview’s paired Geekbench 6 comparison reports the following aggregate scores. It lists 11 Tensor G3 tests and 24 A16 Bionic tests. The results are submitted measurements collected by the comparison site, not scores from a same-lab test conducted for this article. NanoReview’s Tensor G3 vs A16 Bionic comparison

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Geekbench 6 CPU test Tensor G3 A16 Bionic What the result indicates
Single-core 1,722 2,631 A16 Bionic scores higher in this aggregate.
Multi-core 4,458 6,602 A16 Bionic scores higher in this aggregate.

Geekbench’s mobile chart describes its data as user-submitted results gathered through the Geekbench Browser. Its displayed Geekbench 7 entry for the iPhone 14 Pro is 2,368 single-core and 6,412 multi-core. That is a different benchmark generation from Geekbench 6, so it should not be combined with the table above or treated as a direct comparison to the Tensor G3 Geekbench 6 scores. Geekbench mobile benchmarks

How to read the AnTuTu results

NanoReview reports AnTuTu 11 totals of 1,409,016 for Tensor G3 and 1,626,008 for A16 Bionic. The same comparison page warns that Android and iOS AnTuTu results are not directly comparable. Treat these as platform-specific figures rather than proof of a definitive cross-platform performance gap. NanoReview’s Tensor G3 vs A16 Bionic comparison

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AI scores use different phones and frameworks

Geekbench’s AI chart lists Pixel 8 with Tensor G3 using TensorFlow Lite GPU, and iPhone 14 Pro with A16 Bionic using Core ML GPU. The figures are therefore tied to different phones and software frameworks, not a single chip-only test under identical conditions.

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Device and chip Framework and processor Single precision Half precision Quantized
Pixel 8, Tensor G3 TensorFlow Lite GPU 621 721 718
iPhone 14 Pro, A16 Bionic Core ML GPU 3,085 3,343 3,081

Because the frameworks and host devices differ, these values do not establish a universal winner for AI performance. They are most useful as labeled results for those particular device-and-framework combinations. Geekbench AI benchmarks

What the available comparison can—and cannot—tell you

  • CPU benchmark leadership: The paired Geekbench 6 aggregates favor A16 Bionic in both single-core and multi-core scores.
  • Gaming: The cited scores do not directly measure game performance, sustained frame rates, or thermal behavior. They are not enough to declare how every game will run on either phone.
  • Efficiency and battery life: The benchmark figures do not measure battery endurance or power use in everyday conditions.
  • Core count: NanoReview’s secondary comparison lists Tensor G3 as a 9-core design with Mali-G715 MP7 graphics and A16 Bionic as a 6-core chip with Apple GPU. It lists nominal CPU frequencies of 2,910 MHz and 3,460 MHz, respectively. Core count and clock figures alone do not determine performance because the chips have different architectures and workloads. NanoReview’s comparison and specifications
  • Phone features: Charging, memory, software support, cooling, and battery are device-level considerations. For example, Google lists USB-C PD 3.0 (PPS) charging for Pixel 8 and names its 30 W USB-C charger as a separate example; the adapter is sold separately. Google Pixel phone hardware specifications
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Verdict: choose by the performance evidence and the phone

If the question is which chip scores higher in the available paired CPU comparison, the answer is A16 Bionic: it leads Tensor G3 in both Geekbench 6 tests. That is a benchmark-specific conclusion, not a complete ranking of the iPhone 14 Pro and Pixel 8 or a verdict on every workload. The cited material does not provide a controlled same-workload, sustained-performance comparison, so it cannot establish which phone will be faster in every game or remain faster under prolonged load.

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