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Page 4 of AnandTech’s “Google Tensor SoC” thread is a historical enthusiast discussion, not a specification sheet or benchmark report. Posts shown from August 15–16, 2024 debate whether Tensor is “fully self-designed,” whether its CPU and GPU use licensed Cortex and Mali designs, and how modem, storage, process technology and software affect perceived performance. The comments are useful for understanding what enthusiasts questioned at the time, but they do not independently establish Tensor’s architecture or rank Pixel performance.
What the “custom in-house CPU or Cortex?” question means
One participant argues that Google could describe Tensor as self-designed while still using off-the-shelf Arm Cortex CPU cores and Mali GPU technology. The same participant says Samsung LSI and Google’s Silicon team co-designed Tensor at that time. Those are forum-user claims about the contemporary situation in 2024, not independently verified architectural facts and not a description that can safely be applied to every Tensor generation.
“Google-designed” can refer to the system-level chip, the choice and integration of intellectual property, custom accelerators, software, packaging and product goals rather than every CPU or GPU execution core being created from scratch. To answer the question precisely, identify the exact Tensor generation and look for manufacturer documentation or independent die-level analysis; Page 4 does not provide that evidence.
What Tensor is designed to do
Google describes Tensor as a combination of processing resources rather than a CPU-only product. In Google’s plain-language model, the CPU handles general-purpose work, the GPU renders graphics, and the TPU performs on-device artificial-intelligence and machine-learning tasks. These units cooperate on phone features, so a phone’s experience cannot be reduced to a single CPU-core label.
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Google’s original Pixel 6 focus
In its 2021 Tensor introduction, Google framed the first generation around machine-learning features in Pixel 6 and Pixel 6 Pro. Google highlighted on-device translation, computational photography and video processing, and a security design combining the Tensor security core with Titan M2. Google also said its on-device neural-machine-translation model used less than half the power of the corresponding model in earlier Pixel 4-era phones. That was a launch claim for the first Tensor generation, not a current measurement of Tensor G5.
Current product context
Google identifies Tensor G5 as the chip used in the Pixel 10 series and describes it as built on a 3 nm TSMC process. Google says G5 has an up to 60% more powerful TPU and average CPU speed 34% faster than Tensor G4. Both figures are Google’s own comparisons; they are not independent benchmark results and do not by themselves establish an overall performance lead.
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What Page 4 raises—and what it does not prove
| Discussion topic | What appears in the posts | What can responsibly be concluded |
|---|---|---|
| CPU and GPU design | A participant describes Tensor as self-designed while using Cortex CPUs and Mali GPUs, with Samsung LSI and Google Silicon involved. | This is an attributed 2024 forum opinion, not verified documentation for all Tensor generations. |
| Modem behavior | Participants question whether modem performance or reliability explains some Pixel experiences. | The page supplies no controlled modem testing or generation-by-generation reliability result. |
| Storage | Storage technology is discussed as a possible contributor to phone responsiveness. | No standardized storage measurements are established by the thread. |
| Process technology | Users debate node comparisons and what a smaller process should imply. | A process label alone cannot determine real-world speed, efficiency or thermals. |
| Relative performance | Participants disagree about whether Tensor compares favorably with competing chips and whether newer cores guarantee better results. | The page is not a benchmark study and cannot support an overall ranking. |
How to compare Tensor phones without oversimplifying
Use the exact phone and chip generation, then evaluate the workloads that matter to you. A meaningful comparison should separate these axes:
- CPU: app launch, web, productivity and other general-purpose tasks.
- GPU and sustained gaming: frame rates over time, heat and throttling rather than a short peak score.
- On-device AI: translation, voice, photo and other features that actually run on the device.
- Camera and video: image pipelines, HDR processing and recording modes shipped by that phone.
- Modem and connectivity: reception, carrier behavior, battery impact and regional support.
- Power and thermals: battery endurance and sustained temperatures under comparable conditions.
- Software availability: features can vary by model, country, language and carrier.
Checks for a buying comparison
- Record the exact Pixel model and Tensor generation.
- Match RAM and storage configurations before comparing results.
- Check the regional model, supported bands and carrier compatibility; Google notes that connectivity and features can depend on country or carrier.
- Confirm that the AI, camera and network features you care about are available in your language and market.
- Use independent, repeatable measurements for performance or modem claims; treat Google’s percentage improvements as vendor claims.
How to read the thread today
The AnandTech page is valuable as a snapshot of questions enthusiasts were asking in August 2024. It should not be used as a current specification for Tensor G5, a teardown of any Tensor die, proof of modem reliability across Pixel generations, or evidence that one vendor’s chip is universally faster. Google’s current product announcements establish what Google claims about G5 and which phones use it; independent testing is still required for comparative conclusions.
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