Chip comparison
AMD Instinct MI350 series vs Google TPU v5e
Side-by-side specs
Straight from each vendor's datasheet. Winner in bold: higher throughput, memory, or transistor count; lower power draw or price. Sparse (2:4) throughput roughly doubles the FP8/INT8 numbers shown.
| Field | AMD Instinct MI350 series | Google TPU v5e |
|---|---|---|
| Process node | TSMC N3 (chiplet) | — |
| TDP | 1000 W | 170 W |
| Memory | 288 GB HBM3e | 16 GB HBM2 |
| Memory bandwidth | 8,000 GB/s | 819 GB/s |
| FP16 (dense) | 2,300 TFLOPS | — |
| BF16 (dense) | 2,300 TFLOPS | 197 TFLOPS |
| FP8 (dense) | 4,600 TFLOPS | — |
| INT8 (dense) | 4,600 TOPS | 393 TOPS |
| Form factor | OAM | OAM (v5e pod, up to 256 chips) |
| Announced | 2025-06-12 | 2023-08-29 |
| Released | 2025-10-01 | 2023-11-01 |
Robots running AMD Instinct MI350 series
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Robots running Google TPU v5e
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Data centers with AMD Instinct MI350 series
Data centers with Google TPU v5e
Common questions
AMD Instinct MI350 series vs Google TPU v5e: which is faster for training?
AMD Instinct MI350 series has 23.35x the dense FP16/BF16 throughput of the other (AMD Instinct MI350 series: 4,600 TFLOPS; Google TPU v5e: 197 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
AMD Instinct MI350 series vs Google TPU v5e: which has more memory?
AMD Instinct MI350 series carries more HBM (AMD Instinct MI350 series: 288 GB HBM3e; Google TPU v5e: 16 GB HBM2). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
AMD Instinct MI350 series vs Google TPU v5e: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: AMD Instinct MI350 series 4.60 (4,600 ÷ 1000 W); Google TPU v5e 1.16 (197 ÷ 170 W). AMD Instinct MI350 series wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · AMD Instinct MI350 series full page · Google TPU v5e full page.