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GPU comparison · Hopper vs Blackwell Ultra
NVIDIA H200 vs B300.
Hopper against Blackwell Ultra. The B300 has about twice the memory (288 GB against 141 GB of HBM3e), 1.7× the bandwidth, about 2.3× the dense FP8 and BF16 throughput, FP4 tensor cores and NVLink 5. The H200 costs $1,740 less per GPU per month and keeps strong FP64, which the B300 gives up almost entirely.
- 141 vs 288 GBGPU memory
- 4.8 vs 8 TB/smemory bandwidth
- $2,279 vs $4,019per GPU, per month
H200 vs B300: which one to rent.
Choose the H200 if
- Your models fit in 141 GB per GPU: up to about 108B parameters in FP8 by our sizing rule, or a 70B model with about 45 GB to spare for context.
- You run FP64 simulation: 34 TFLOPS of FP64 (67 on tensor cores) against 1.25 on the B300.
- You want the lower monthly price: $2,279 per GPU against $4,019.
Choose the B300 if
- Your model needs more than 141 GB per GPU: one B300 holds about 220B parameters in FP8, against about 108B on an H200.
- You want FP4 or more throughput: 13.5 PFLOPS of dense FP4 and about 2.3× the dense FP8 of the H200.
- You train across 8 GPUs: NVLink 5 moves 1.8 TB/s per GPU, twice NVLink 4.
H200 vs B300 specs, side by side.
Figures from NVIDIA’s published specifications, per GPU. Tensor figures are peak dense throughput.
| Per GPU | NVIDIA H200 | NVIDIA B300 | B300 / H200 |
|---|---|---|---|
| Architecture | Hopper | Blackwell Ultra, TSMC 4NP | — |
| Form factor | SXM module | SXM module (HGX B300) | — |
| GPU memory | 141 GB HBM3e | 288 GB HBM3E | 2× |
| Memory bandwidth | 4.8 TB/s | Up to 8 TB/s | 1.67× |
| GPU-to-GPU link | NVLink 4, 900 GB/s per GPU | NVLink 5, 1.8 TB/s per GPU | 2× |
| FP4 tensor (dense) | Not supported | 13.5 PFLOPS | — |
| FP8 tensor (dense) | 1,979 TFLOPS | 4,500 TFLOPS | 2.3× |
| FP16 / BF16 tensor (dense) | 989 TFLOPS | 2,250 TFLOPS | 2.3× |
| FP64 | 34 / 67 TFLOPS | 1.25 TFLOPS | 0.04× |
| Max power | Up to 700 W, configurable | Not published | — |
| GPUs per server | 1, 2, 4, 8 | 1, 2, 4, 8 | — |
| Per GPU in our servers | 24 vCPU · 256 GB RAM · 3.84 TB | 32 vCPU · 384 GB RAM · 3.84 TB | — |
Sources: NVIDIA H200 · NVIDIA HGX · Blackwell Ultra technical blog. Full sheets: H200 · B300
H200 vs B300 rental price.
At CryptGPU, the H200 rents for $2,279 and the B300 for $4,019 per GPU per month, 30% below the market median of public on-demand prices, paid in crypto with no KYC. Hourly figures are the monthly price divided by 730 hours.
| CryptGPU | NVIDIA H200 | NVIDIA B300 | B300 / H200 |
|---|---|---|---|
| Price per GPU, per month | $2,279 | $4,019 | 1.76× |
| Equivalent per GPU-hour | $3.12 | $5.51 | — |
| Per GB of GPU memory, per month | $16.16 | $13.95 | 0.86× |
| Per PFLOPS of dense FP8, per month | $1,152 | $893 | 0.78× |
| Largest server | 8× · $18,232/mo | 8× · $32,152/mo | — |
| Market median, per GPU | $3,259 | $5,745 | — |
| Below the median | −30% | −30% | — |
Same price per GPU at every server size, no hourly metering. How we compare prices · Configure an H200 server · Configure a B300 server
Which models fit on each.
Smallest server that holds each model, by precision. Rule of thumb with headroom for the KV cache, 92% of GPU memory usable.
| Model (total parameters) | H200 · FP8 | B300 · FP8 | H200 · 4-bit | B300 · 4-bit |
|---|---|---|---|---|
| Qwen3.5-9B | 1× | 1× | 1× | 1× |
| Gemma 4 31B | 1× | 1× | 1× | 1× |
| Llama 3.3 70B | 1× | 1× | 1× | 1× |
| gpt-oss-120b | 2× | 1× | 1× | 1× |
| DeepSeek-V4-Flash | 4× | 2× | 2× | 1× |
| Qwen3.5-397B-A17B | 4× | 2× | 2× | 1× |
| DeepSeek-R1 (671B) | 8× | 4× | 4× | 2× |
| Kimi K2.6 (1T) | — | 8× | 8× | 4× |
FP8 ≈ 1.2 bytes and 4-bit ≈ 0.65 bytes per parameter. — = larger than the biggest server of that GPU. Size another model · How much VRAM does an LLM need?
H200 vs B300 FAQ.
More on each GPU: NVIDIA H200 · NVIDIA B300.
Is the B300 worth the extra cost over the H200?
Per GB of memory and per unit of compute it costs less: $13.95 per GB a month against $16.16, and about $893 per PFLOPS of dense FP8 against $1,152. If your models fit on H200s and their speed is enough, the H200 costs less per GPU.
Does the B300 run FP64 workloads?
Barely: Blackwell Ultra keeps 1.25 TFLOPS of FP64, against 34 on the H200 (67 on its tensor cores). For FP64 simulation, choose the H200, the H100 or the AMD MI355X.
What fits in an 8-GPU server?
1,128 GB on 8× H200 against 2,304 GB on 8× B300. By our rule of thumb, a 671B model in FP8 (about 805 GB) fits on either; in BF16 (about 1,610 GB) it fits only on the B300 server.
Other GPU comparisons.
Rent the H200 or the B300.
Dedicated servers with 1 to 8 GPUs, one monthly price, paid in crypto. Online in under 10 minutes, no KYC.