Chip comparison
Google TPU v6 (Trillium) vs NVIDIA Jetson AGX Orin
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 | Google TPU v6 (Trillium) | NVIDIA Jetson AGX Orin |
|---|---|---|
| Process node | — | Samsung 8N |
| TDP | 200 W | 60 W |
| Memory | 32 GB HBM3 | 64 GB LPDDR5 |
| Memory bandwidth | 1,600 GB/s | 204.8 GB/s |
| BF16 (dense) | 918 TFLOPS | — |
| FP8 (dense) | 1,836 TFLOPS | — |
| INT8 (dense) | 1,836 TOPS | 275 TOPS |
| Form factor | OAM (Trillium pod, up to 256 chips) | Module (AGX Orin 64GB) |
| Announced | 2024-05-14 | 2022-03-22 |
| Released | 2024-12-01 | 2022-07-01 |
Robots running Google TPU v6 (Trillium)
No robots publicly running it yet.
Robots running NVIDIA Jetson AGX Orin
Data centers with Google TPU v6 (Trillium)
Data centers with NVIDIA Jetson AGX Orin
No data centers publicly running it yet.
Common questions
Google TPU v6 (Trillium) vs NVIDIA Jetson AGX Orin: which has more memory?
NVIDIA Jetson AGX Orin carries more HBM (Google TPU v6 (Trillium): 32 GB HBM3; NVIDIA Jetson AGX Orin: 64 GB LPDDR5). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Google TPU v6 (Trillium) vs NVIDIA Jetson AGX Orin: which is more widely used?
Google TPU v6 (Trillium): 0 robots and 1 data center publicly running it. NVIDIA Jetson AGX Orin: 9 robots and 0 data centers. Empty here means no operator has said publicly, not zero adoption in the market.
See also: every chip comparison · Google TPU v6 (Trillium) full page · NVIDIA Jetson AGX Orin full page.