Chip comparison
Groq LPU (Language Processing Unit) vs NVIDIA T4 Tensor Core GPU
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 | Groq LPU (Language Processing Unit) | NVIDIA T4 Tensor Core GPU |
|---|---|---|
| Process node | GlobalFoundries 14nm | TSMC 12FFN |
| Transistors (B) | — | 13.6 |
| Die size | — | 545 mm² |
| TDP | 375 W | 70 W |
| Memory | 0.23 GB SRAM (230 MB on-die) | 16 GB GDDR6 |
| Memory bandwidth | 80,000 GB/s | 320 GB/s |
| FP16 (dense) | 188 TFLOPS | 65 TFLOPS |
| INT8 (dense) | 750 TOPS | 130 TOPS |
| Form factor | PCIe (GroqCard) / rack-scale GroqRack | PCIe (single-slot, low-profile) |
| Announced | 2020-01-01 | 2018-09-13 |
| Released | 2021-06-01 | 2019-01-01 |
Robots running Groq LPU (Language Processing Unit)
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Robots running NVIDIA T4 Tensor Core GPU
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Data centers with Groq LPU (Language Processing Unit)
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Data centers with NVIDIA T4 Tensor Core GPU
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Common questions
Groq LPU (Language Processing Unit) vs NVIDIA T4 Tensor Core GPU: which is faster for training?
Groq LPU (Language Processing Unit) has 2.89x the dense FP16/BF16 throughput of the other (Groq LPU (Language Processing Unit): 188 TFLOPS; NVIDIA T4 Tensor Core GPU: 65 TFLOPS). Real-world training speed also depends on memory bandwidth, interconnect, and software stack: see the spec diff for those inputs.
Groq LPU (Language Processing Unit) vs NVIDIA T4 Tensor Core GPU: which has more memory?
NVIDIA T4 Tensor Core GPU carries more HBM (Groq LPU (Language Processing Unit): 0.23 GB SRAM (230 MB on-die); NVIDIA T4 Tensor Core GPU: 16 GB GDDR6). Memory capacity sets the largest model that fits on one chip without partitioning; memory bandwidth sets inference throughput.
Groq LPU (Language Processing Unit) vs NVIDIA T4 Tensor Core GPU: which is more power-efficient?
Dense FP16/BF16 TFLOPS per watt: Groq LPU (Language Processing Unit) 0.50 (188 ÷ 375 W); NVIDIA T4 Tensor Core GPU 0.93 (65 ÷ 70 W). NVIDIA T4 Tensor Core GPU wins at the die level; system-level efficiency also depends on cooling and interconnect.
See also: every chip comparison · Groq LPU (Language Processing Unit) full page · NVIDIA T4 Tensor Core GPU full page.