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Apple’s A15 Bionic has published CPU, GPU and Neural Engine details; Google identifies Tensor G6 as the chip in Pixel 11 phones but does not publish a comparable specification table on its Tensor overview. One review reports Pixel 11 Geekbench 6 scores, but there is no matched A15 result in the available evidence. That means the figures support a careful comparison—not a defensible overall benchmark winner.
At a glance: specifications and evidence
| Chip | Confirmed platform details | Available benchmark evidence |
|---|---|---|
| Apple A15 Bionic | 6-core CPU; 16-core Neural Engine; 4-core or 5-core GPU depending on device. Apple lists A15 in iPhone 13-family models. | Apple reports 15.8 teraflops peak throughput for the 16-core Neural Engine in iPhone 13 Pro. This is a vendor-reported peak, not a cross-platform AI benchmark. |
| Google Tensor G6 | Google says Tensor G6 powers Pixel 11 phones and the newest Gemini Nano model. The official overview does not provide a full CPU, GPU, clock-speed, or process-node specification. | Tom’s Guide reports Pixel 11 averages of 2,664 single-core and 7,347 multi-core in Geekbench 6. These are device-level review results, not a matched A15 comparison. |
Sources: Apple iPhone comparison, Google Tensor overview, Apple Machine Learning Research, and Tom’s Guide Pixel 11 review.
What the A15 Bionic specifications tell you
CPU and device variation
Apple lists the A15 with a 6-core CPU and a 16-core Neural Engine. The GPU configuration is not identical across A15 devices: some have four GPU cores and others five. Name the phone when giving a GPU count rather than treating one configuration as universal.
Apple’s comparison material lists A15 on iPhone 13-family models. The chip specification alone does not describe how a particular phone performs in every app or under sustained load.
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Apple’s GPU statement
Apple Developer describes the A15 GPU as having up to five shader cores. In a presentation, Dave Roberts of Apple’s GPU Software team said the fifth core provides a 25% performance boost “at the same GPU core frequency.” That is Apple’s stated comparison of A15 GPU configurations, not a measured advantage over Tensor G6. Apple Developer: Discover advances in Metal for A15 Bionic.
Neural Engine throughput
Apple Machine Learning Research reports peak throughput of 15.8 teraflops for the 16-core Neural Engine in the iPhone 13 Pro’s A15, and says that figure is 26 times that of iPhone X. Treat it as Apple’s peak figure for that device and chip, not a general real-world throughput guarantee or a direct comparison with Google’s TPU. Apple Machine Learning Research.
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What is confirmed about Tensor G6
Google says Tensor G6 is in Pixel 11 phones and powers the newest Gemini Nano model, which Google describes as its most advanced AI on a phone. Google also characterizes Tensor as a system-on-chip designed to run machine-learning and generative-AI work on Pixel phones. Google’s Tensor overview.
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The official overview does not give a detailed Tensor G6 CPU configuration, clock speeds, GPU architecture, process node, or standardized benchmark score. Accordingly, leaked or otherwise unconfirmed specifications should not be presented as official facts.
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Tensor G6 benchmark results: what Geekbench 6 says
Tom’s Guide reports average Geekbench 6 scores of 2,664 single-core and 7,347 multi-core for the Pixel 11 with Tensor G6. These are results for a complete phone, not an isolated chip: device hardware, software and test conditions are part of the result. The review figures are useful as a reported Pixel 11 datapoint, but they do not establish how Tensor G6 ranks against A15.
A fair head-to-head requires scores produced using the same benchmark version and comparable test conditions on named devices. Do not calculate a percentage lead by comparing the Pixel 11 figures with A15 scores from a different phone, software build, review or test method. Tom’s Guide Pixel 11 review.
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How to compare the chips fairly
- CPU: A15’s 6-core CPU is documented, but the evidence here does not establish a matched CPU benchmark against Tensor G6.
- GPU: Apple supplies A15 GPU configuration details and a same-frequency claim about its fifth core; the reviewed official Google material does not disclose Tensor G6 GPU specifics.
- On-device AI: Google identifies Gemini Nano support on Tensor G6, while Apple reports a peak Neural Engine throughput figure for A15 in iPhone 13 Pro. These describe different capabilities and are not results from a shared AI test.
- Whole-device performance: The Pixel 11 Geekbench scores are phone-level averages from one review. Without an A15 phone tested comparably, they cannot determine a direct ranking.
- Sustained performance and efficiency: A meaningful comparison would need comparable thermal, battery and sustained-workload testing. The figures above do not establish those outcomes.
When reviewing a benchmark claim, look for the benchmark and version, exact phone, software or build, score type, whether the number is an average or a single run, and test date. Keep CPU, graphics, AI and sustained workloads separate; one score cannot stand in for all four.
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Which chip should you choose?
The chip names alone do not settle which phone is the better choice. A15 has more publicly specified hardware details in the sources cited here, while Google’s confirmed Tensor G6 messaging emphasizes Pixel 11 and Gemini Nano. The one available Tensor G6 benchmark datapoint is not a controlled A15-versus-G6 test. Choose between an A15-equipped iPhone and a Tensor G6 Pixel based on the phone, software and features you need; do not treat these figures as proof of an overall silicon winner.
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