B200 vs MI355X

Detailed comparison of specifications, performance, and pricing between NVIDIA B200 and AMD Instinct MI355X

🏆
Overall Winner
B200
Wins 3 of 7 categories
Performance Leader
B200
4.5k TFLOPS (+0%)
💰
Price Leader
MI355X
$$25k (80% cheaper)

Difference Analysis

Metric
B200
Difference
MI355X
Tensor TFLOPS
4.5k
=
-
VRAM
192GB
-50%
288GB
Memory Bandwidth
8.0 TB/s
=
8.0 TB/s
Hardware Price
$$45k
+80%
$$25k
Cloud Price/hr
$3.75
=
-

Full Specifications

Specification B200 MI355X
Brand NVIDIA AMD
Series Data Center Data Center
Architecture Blackwell CDNA4
VRAM 192GB 288GB
VRAM Type HBM3e HBM3e
Memory Bandwidth 8.0 TB/s 8.0 TB/s
FP16 TFLOPS - -
Tensor TFLOPS 4.5k -
TDP 1000W 500W
Form Factor SXM OAM
Hardware Price $$45k $$25k
Cloud Price (min) $3.75/hr -

Which Should You Choose?

🧠

For AI Training

Large model training needs maximum VRAM and memory bandwidth.

Recommended: MI355X
288GB VRAM · 8.0 TB/s

For AI Inference

Inference prioritizes throughput and cost efficiency.

Recommended: B200
Best performance per dollar
💰

On a Budget

Get the most capability for your money.

Recommended: MI355X
$$25k · 80% cheaper

B200 vs MI355X FAQ

It depends on your use case. The B200 offers 0% better performance (4.5k vs - TFLOPS). However, the MI355X is 80% cheaper. For raw performance, choose B200. For value, consider your budget and workload requirements.

The MI355X has more VRAM with 288GB compared to 192GB (50% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.

For AI training, the MI355X is generally better due to its larger VRAM (288GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 192GB, the cheaper option may be more cost-effective.

The MI355X is 80% cheaper at $$25k vs $$45k. When considering performance per dollar, evaluate your specific workload requirements to determine the best value.

Upgrading to B200 would give you 0% more performance and similar VRAM. The upgrade cost difference is approximately $$20k. Consider if your workloads are bottlenecked by current GPU capabilities.