B200 vs L40

Detailed comparison of specifications, performance, and pricing between NVIDIA B200 and L40

🏆
Overall Winner
B200
Wins 4 of 7 categories
Performance Leader
B200
4.5k TFLOPS (+0%)

Difference Analysis

Metric
B200
Difference
L40
Tensor TFLOPS
4.5k
=
-
VRAM
192GB
+300%
48GB
Memory Bandwidth
8.0 TB/s
=
-
Hardware Price
$$45k
=
-
Cloud Price/hr
$3.75
+295%
$0.950

Full Specifications

Specification B200 L40 AMD Instinct MI100
Brand NVIDIA NVIDIA AMD
Series Data Center - Data Center
Architecture Blackwell - CDNA
VRAM 192GB 48GB 32GB
VRAM Type HBM3e - HBM2
Memory Bandwidth 8.0 TB/s - 1.2 TB/s
FP16 TFLOPS - - 184.6
Tensor TFLOPS 4.5k - 184.6
TDP 1000W - 300W
Form Factor SXM - -
Hardware Price $$45k - -
Cloud Price (min) $3.75/hr $0.950/hr -

Which Should You Choose?

🧠

For AI Training

Large model training needs maximum VRAM and memory bandwidth.

Recommended: B200
192GB VRAM · 8.0 TB/s

For AI Inference

Inference prioritizes throughput and cost efficiency.

Recommended: B200
Best performance per dollar
☁️

For Cloud Rental

Minimize hourly costs for cloud workloads.

Recommended: L40
From $0.950/hr

B200 vs L40 FAQ

It depends on your use case. The B200 offers 0% better performance (4.5k vs - TFLOPS). For raw performance, choose B200. For value, consider your budget and workload requirements.

The B200 has more VRAM with 192GB compared to 48GB (300% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.

For AI training, the B200 is generally better due to its larger VRAM (192GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 48GB, the cheaper option may be more cost-effective.

Price comparison requires both GPUs to have available pricing data. Check individual GPU pages for current market prices.

Upgrading to B200 would give you 0% more performance and 300% more VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.