~/gpu/b200 vs h100

B200 manufacturerB200vsH100 80GB manufacturerH100 80GB

Head-to-head for local LLM inference. The honest comparison: VRAM, bandwidth, compute, and which of the 30 catalog models actually fit on each.

The specs.

$ diff specs b200 h100
Stat
b200
h100
Δ
VRAM
192 GB
80 GB
-58%
Memory bandwidth
8,000 GB/s
3,350 GB/s
-58%
FP16 compute
2250 TFLOPS
989 TFLOPS
-56%
Weights budget at 8K ctx
154 GB
63 GB
-59%

Model fit difference.

$ models that change with the card
Fits on both
27of 30
Only on b200
0
Only on h100
0

// showing 12 of 30 models; differing fits first

Model
b200
h100
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsQ6_K
overQ4_K_M
overQ4_K_M
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsQ8_0
fitsFP16/BF16
fitsQ8_0
fitsFP16/BF16
fitsQ6_K
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16
fitsFP16/BF16

Which one wins for…

$ ./recommend --by-workload
More VRAM headroom

B200 has 112 GB more.

Faster decode (bandwidth)

B200 by +139%.

Faster prefill (compute)

B200 by +128% TFLOPS.

Catalog models that fit

Tied: 27 of 30 fit on each.

Drill into either card.

$ ./vrambudget --gpu

Discussion.

$ gh discussion list

// sign in with github to leave a comment. threads live in the repo's discussions tab.