Google TPU v6e 32GB vs Google TPU v5e 16GB
The TPU v6e delivers 4.7x the BF16 throughput of the TPU v5e (918 vs 197 TFLOPS dense). The TPU v6e also carries 16 GB more memory (32 GB vs 16 GB).
Google TPU v6e 32GB
Full specs →Google TPU v5e 16GB
Full specs →Specifications
Performance (TFLOPS)
FLOPS by Precision
What actually differs
The TPU v6e is the newer part: TPU, launched in 2024, against the TPU v5e's TPU from 2023. Newer architectures typically add lower-precision formats and better throughput per watt, so check the precision rows your workload actually uses.
Memory is 32 GB against 16 GB, fed at 1.6 TB/s versus 800 GB/s. More memory per GPU means larger models fit before you have to shard across cards, which often matters more than raw TFLOPS for inference.
For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.
Frequently asked questions
Is the TPU v6e faster than the TPU v5e?
At BF16 precision the TPU v6e reaches 918 TFLOPS dense against 197 TFLOPS for the TPU v5e. The performance table on this page lists every published precision for both GPUs.
Which has more memory, the TPU v6e or the TPU v5e?
The TPU v6e carries 32 GB of VRAM versus 16 GB for the TPU v5e. Memory bandwidth is 1.6 TB/s for the TPU v6e and 800 GB/s for the TPU v5e.
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