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Apple’s A16 Bionic scores higher than Google’s Tensor G3 in the paired Geekbench 6 results available for comparison. NanoReview reports 2,631 versus 1,722 in single-core and 6,602 versus 4,458 in multi-core. Those are submitted benchmark aggregates, not controlled tests of the chips under identical phone conditions, so they do not establish which phone is better overall or how either chip performs in every workload.
Which chip is faster?
For CPU performance in NanoReview’s paired Geekbench 6 comparison, the A16 Bionic leads in both single-core and multi-core scores. That gives a clear result for that benchmark and version, but not a universal verdict on speed, efficiency, gaming, sustained performance, or overall phone quality.
The chip-to-phone context matters: Google lists Tensor G3 in the Pixel 8 family, while the A16 Bionic is associated here with the iPhone 14 Pro. Phone design, operating system, cooling, memory, and software can affect what a benchmark measures; results from these devices are not a controlled chip-only experiment.
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NanoReview’s paired comparison reports these Geekbench 6 aggregates. The page lists 11 Tensor G3 tests and 24 A16 Bionic tests; the figures are submitted results, not measurements performed for this article.
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| Geekbench 6 test | Tensor G3 | A16 Bionic | Result in this comparison |
|---|---|---|---|
| Single-core | 1,722 | 2,631 | A16 Bionic scores higher |
| Multi-core | 4,458 | 6,602 | A16 Bionic scores higher |
Geekbench single-core and multi-core scores describe different CPU workloads. Neither should be treated as a direct measure of graphics performance, battery life, or how fast a phone will remain during a long, demanding session. The comparison page also lists the Tensor G3 as a 9-core design and the A16 as a 6-core chip, but core counts alone do not predict speed: the Geekbench results favor the A16 despite its lower reported count. These design details and reported nominal frequencies—2,910 MHz for Tensor G3 and 3,460 MHz for A16—come from NanoReview, rather than manufacturer documentation.
How to read the other benchmark figures
AnTuTu 11
NanoReview reports AnTuTu 11 totals of 1,409,016 for Tensor G3 and 1,626,008 for A16 Bionic. However, NanoReview explicitly cautions: “AnTuTu results from iOS and Android are not directly comparable!” Treat these as platform-specific reported scores, not decisive evidence that one chip is faster across platforms.
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Geekbench 7
Geekbench’s mobile chart shows the iPhone 14 Pro A16 entry at 2,368 single-core and 6,412 multi-core in Geekbench 7. Geekbench says its chart data comes from user-submitted results. These figures are from a different benchmark generation than the Geekbench 6 comparison above; do not compare the numbers across versions as if they were scores from the same test.
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AI benchmarks
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 reported single-precision, half-precision, and quantized scores are respectively 621, 721, and 718 for the Pixel entry, and 3,085, 3,343, and 3,081 for the iPhone entry. Because the device and framework differ, these figures do not provide a direct chip-only comparison; a simple score ratio or universal AI winner would be misleading.
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What the specifications do—and do not—tell you
Google’s Pixel 8 hardware specifications identify Tensor G3 as the phone’s processor and list 8 GB LPDDR5X memory for the device. That RAM figure belongs to the Pixel 8, not to the Tensor G3 chip specification. Similarly, Google’s listed charging support—USB-C PD 3.0 (PPS)—and its seven-year update commitment for Pixel 8 and Pixel 8 Pro are phone-level details, not properties of the processor.
Google counts the seven years of updates from the first US Google Store availability of Pixel 8 and Pixel 8 Pro. These device features may matter when choosing between phones, but they do not alter the Geekbench result or establish chip efficiency, battery endurance, or thermal behavior.
Rank #4
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Which one should you choose?
- For the benchmark comparison shown here: A16 Bionic leads in both Geekbench 6 CPU tests.
- For cross-platform AnTuTu: do not use the listed totals as a definitive ranking; the source warns the Android and iOS scores are not directly comparable.
- For AI performance: the listed Geekbench entries use different frameworks and phones, so they cannot settle a chip-only contest.
- For a phone purchase: compare the actual Pixel 8 and iPhone 14 Pro features, support, and software alongside processor benchmarks. These figures alone do not determine overall device value or sustained performance.
Sources and benchmark context
- Google Pixel phone hardware tech specs identifies the Pixel 8 processor and gives phone-level memory, charging, and update information.
- Geekbench Mobile Benchmarks describes its mobile chart as based on user-submitted results.
- NanoReview’s Tensor G3 vs A16 Bionic comparison provides the paired Geekbench 6 and AnTuTu figures and the cross-platform AnTuTu caveat.
- Geekbench AI Benchmarks lists the device- and framework-specific AI entries.
Benchmark submissions can change over time. The figures above reflect the cited chart and comparison pages checked on October 7, 2026.
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