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Google Cloud TPU v5p

By Google Cloud →

Most powerful TPU supercomputer built for large-scale bio-foundation models

Cloud TPU v5p is Google’s flagship AI accelerator, delivering 459 TFLOPS of bfloat16 performance and 95 GB of High Bandwidth Memory (HBM2e) per chip, scaling to 8,960-chip pods with optical circuit switches.

4x larger scalability compared to TPU v4, reaching up to 8,960 chips per pod95 GB of high-bandwidth memory enabling massive batch sizes for protein transformers4,800 Gbps inter-chip interconnect per pod for ultra-fast all-reduce communicationSupported natively by JAX, TensorFlow, and PyTorch (via PyTorch/XLA)
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Overview

Cloud TPU v5p is Google’s flagship AI accelerator, delivering 459 TFLOPS of bfloat16 performance and 95 GB of High Bandwidth Memory (HBM2e) per chip, scaling to 8,960-chip pods with optical circuit switches.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 20/09/2026, 11:10:15

Key Features

  • 4x larger scalability compared to TPU v4, reaching up to 8,960 chips per pod
  • 95 GB of high-bandwidth memory enabling massive batch sizes for protein transformers
  • 4,800 Gbps inter-chip interconnect per pod for ultra-fast all-reduce communication
  • Supported natively by JAX, TensorFlow, and PyTorch (via PyTorch/XLA)

Academic Context & Research Evidence

Biological & Workflow Fit

Biological Application
Training AlphaFold models, genomic transformers (Enformer, Borzoi), and multi-modal bio-models
Research Workflow
Distributed model training across TPU pods in Google Cloud Platform
Compute & Hardware
Google Cloud Platform (GCP) project with TPU quota
Licensing & Academic Use
Google Cloud Platform service terms
Documented Evidence
View validation publication / source ↗

Cite this Tool

Use this citation format when referencing Google Cloud TPU v5p in scientific publications and benchmark papers.

@software{google_tpu_v5p_2026,
  title = {{Google Cloud TPU v5p}},
  author = {{Google Cloud}},
  year = {2026},
  url = {https://cloud.google.com/tpu},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for Google Cloud TPU v5p.

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Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeCloud Hardware Accelerator
Access modeCloud On-Demand & Spot Pricing
AI roleDeep Learning Supercomputing
Input dataNot recorded
Output dataNot recorded
Licence conditionsGoogle Cloud Platform service terms
Commercial eligibilityCommercial cloud access
Compute requirementsGoogle Cloud Platform (GCP) project with TPU quota
ValidationNot recorded
TypeApplication-Specific Integrated Circuit (ASIC)
Intended useNot recorded
CompatibilityNot recorded
ManufacturerGoogle LLC
Biological applicationTraining AlphaFold models, genomic transformers (Enformer, Borzoi), and multi-modal bio-models
Research workflowDistributed model training across TPU pods in Google Cloud Platform
Evidence levelHardware foundation for Google DeepMind AlphaFold and AlphaMissense research
Integration evidencehttps://cloud.google.com/tpu/docs/v5p
Laboratory handoffProvides scalable training compute for computational biology teams
AvailabilityAvailable via Google Cloud Platform
Price / accessCloud compute — pay per chip-hour

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

No licensed product photograph recorded for Google Cloud TPU v5p yet. Visit the official resource below for manufacturer imagery.

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Alternatives

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FAQ

Where is this product available?

Available via Google Cloud Platform

How is pricing handled?

Prices reflect the source at its last check. Confirm current pricing and regional availability on the official site.

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating Google Cloud TPU v5p.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5