NVIDIA B100 SXM 192GB vs NVIDIA GB200 Grace Blackwell Superchip 372GB
The GB200 delivers 2.9x the FP8 throughput of the B100 (10,000 vs 3,500 TFLOPS dense). The GB200 also carries 180 GB more memory (372 GB vs 192 GB).
NVIDIA B100 SXM 192GB
Full specs →NVIDIA GB200 Grace Blackwell Superchip 372GB
Full specs →Specifications
Performance (TFLOPS)
FLOPS by Precision
What actually differs
Both GPUs launched in 2024: the B100 on Blackwell and the GB200 on Blackwell.
Dense throughput for the B100 against the GB200: FP64 30 vs 80 TFLOPS, FP32 60 vs 160 TFLOPS, FP16 1,750 vs 5,000 TFLOPS, FP8 3,500 vs 10,000 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.
Memory is 192 GB against 372 GB, fed at 8.0 TB/s versus 16.0 TB/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 B100 faster than the GB200?
At FP8 precision the GB200 reaches 10,000 TFLOPS dense against 3,500 TFLOPS for the B100. The performance table on this page lists every published precision for both GPUs.
Which has more memory, the B100 or the GB200?
The GB200 carries 372 GB of VRAM versus 192 GB for the B100. Memory bandwidth is 8.0 TB/s for the B100 and 16.0 TB/s for the GB200.
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