Rent the B200 if…
you pre-train or post-train large models, serve at FP4 or FP8 with big batches, or need between 80 and 180 GB per GPU — the B200 finishes the same job with fewer GPUs.
Deploy a B200 · $2,690/mo
NVIDIA B200180 GB HBM3e · Blackwell
vs
NVIDIA H100 SXM80 GB HBM3 · Hopper
NVIDIA B200 vs H100: is Blackwell worth it?
Blackwell against Hopper: 180 GB of HBM3e at 8 TB/s, about 2.3× the dense tensor throughput and the new FP4 format on the B200, against 80 GB at 3.35 TB/s on the H100 SXM — for 2.2× the monthly price.
- B200, dedicated$2,690per month · $3.68/h effective
- H100, dedicated$1,249per month · $1.71/h effective
- Price ratio2.2×the B200 costs 2.2× the H100 per month
The short answer
Which one should you rent?
Per GPU, the B200 does more than twice the work of an H100 and holds more than twice the data: 2.2× the price for about 2.3× the compute, 2.25× the memory and 2.4× the bandwidth. For frontier training, FP4 and FP8 inference at scale, and models between 80 and 180 GB, it is the better buy per result. The H100 stays the sensible choice when your model fits in 80 GB, your stack is tuned for Hopper, or the job is short enough that $1,249 a month matters more than the hours saved.
- Compute. About 2,250 TFLOPS of dense FP16/BF16 and 4,500 of FP8 on the B200, against about 989 and 1,979 on the H100 SXM — plus about 9,000 TFLOPS of FP4, a format Hopper cannot use.
- Memory. 180 GB of HBM3e at 8 TB/s against 80 GB of HBM3 at 3.35 TB/s: a 70B model fits on one B200 at 16-bit, with 40 GB to spare.
- NVLink. Fifth-generation NVLink at 1.8 TB/s per GPU, twice the H100's 900 GB/s: tensor-parallel jobs across an 8-GPU node spend less time waiting on each other.
- Software. Blackwell needs CUDA 12.8 or later and recent framework builds; FP4 needs libraries that support it. Hopper runs everything published in the last three years.
Rent the H100 if…
your model fits in 80 GB, your kernels and containers are tuned for Hopper, or you want the most mature software support at the lower monthly price.
Deploy an H100 · $1,249/moSpecifications
B200 vs H100: the numbers side by side
NVIDIA's published figures for each part, tensor throughput without sparsity. The last column is how the B200 compares, as a multiple of the H100.
| Specification | NVIDIA B200 | NVIDIA H100 SXM | B200 vs H100 |
|---|---|---|---|
| Architecture | Blackwell · 2024 | Hopper · 2022 | — |
| GPU memory | 180 GB HBM3e | 80 GB HBM3 | 2.3× |
| Memory bandwidth | 8 TB/s | 3.35 TB/s | 2.4× |
| FP16 / BF16 tensor (dense) | ~2,250 TFLOPS | ~989 TFLOPS | 2.3× |
| FP8 tensor (dense) | ~4,500 TFLOPS | ~1,979 TFLOPS | 2.3× |
| FP4 tensor (dense) | ~9,000 TFLOPS | Not supported | Only the B200 |
| Maximum power | Up to 1,000 W | Up to 700 W | 1.4× |
| Form factor | SXM (HGX B200) | SXM5 | — |
| GPU-to-GPU link | NVLink 5 · 1.8 TB/s | NVLink 4 · 900 GB/s | — |
| Multi-Instance GPU (MIG) | Up to 7 instances | Up to 7 instances | — |
| ECC memory | Yes | Yes | — |
| Video engines | 7 NVDEC · 7 NVJPG | 7 NVDEC · 7 NVJPG | — |
| CUDA compute capability | 10.0 | 9.0 | — |
| Dedicated host here | 32 vCPU · 384 GB RAM · 4 TB NVMe | 24 vCPU · 256 GB RAM · 3 TB NVMe | — |
| Price per month here | $2,690 | $1,249 | 2.2× |
Sources: NVIDIA datasheets and product pages for each GPU. Tensor figures are dense (NVIDIA often prints them doubled “with sparsity”). Prices are this site's flat monthly rates for a dedicated server with the host listed, in USD excluding VAT.
Value
What each dollar buys
Price per month divided into the two resources most jobs run out of first — memory and memory bandwidth — and what the same GPU costs kept on for a month at the market-median hourly rate.
Per GB of GPU memoryB200 $14.94 · H100 $15.61per month, dedicated host included
Per TB/s of bandwidthB200 $336 · H100 $373per month — what decode-heavy inference pays for
Effective hourly rateB200 $3.68/h · H100 $1.71/hflat monthly price over 730 hours
Same GPU on demand, 24/7B200 $5,220 · H100 $2,446market-median hourly rate × 730 h
Model sizes
What fits on one B200 and one H100
The largest model whose weights fit on a single GPU, keeping 10% of the memory for the runtime, activations and a small KV cache. Long contexts and large batches need more — size them with the GPU memory calculator.
| Weights precision | NVIDIA B200 | NVIDIA H100 SXM | Typical use |
|---|---|---|---|
| 16-bit (BF16 / FP16) | up to ~81B parameters | up to ~36B parameters | Full-precision inference; the base weights of a LoRA fine-tune |
| 8-bit (FP8 / INT8) | up to ~160B parameters | up to ~72B parameters | FP8 serving with vLLM or TensorRT-LLM on GPUs that support it; INT8 weights elsewhere |
| 4-bit (GPTQ, AWQ, Q4) | up to ~290B parameters | up to ~130B parameters | Quantised inference on a budget; QLoRA fine-tuning |
Parameters in billions, weights only: 2 bytes per parameter at 16-bit, 1 at FP8 or INT8, about 0.55 at 4-bit (GPTQ, AWQ, GGUF Q4). Mixture-of-experts models need memory for all their experts, not just the active ones.
Prices
B200 and H100 price per month, by term
Per dedicated GPU server, in USD excluding VAT — CPU cores, RAM, NVMe, 20 TB of transfer and 24/7 support included.
| Term | NVIDIA B200 | NVIDIA H100 SXM | Difference per month |
|---|---|---|---|
| Monthly | $2,690 | $1,249 | $1,441 |
| 3 months · −5% | $2,556 | $1,187 | $1,369 |
| 6 months · −10% | $2,421 | $1,124 | $1,297 |
| 12 months · −15% | $2,287 | $1,062 | $1,225 |
| Dedicated host | 32 vCPU · 384 GB RAM · 4 TB NVMe · 25 Gbps | 24 vCPU · 256 GB RAM · 3 TB NVMe · 25 Gbps | included |
B200 vs H100: questions answered
How much faster is the B200 than the H100?
On paper, about 2.3× at FP16 and FP8 per GPU, with FP4 on top. Real speedups depend on the model and the software stack; jobs that were bound by memory can gain more, because work that needed two H100s may fit on one B200.
Does H100 code run on the B200?
Yes, with a recent toolkit: Blackwell is supported from CUDA 12.8, with framework builds compiled for it (PyTorch, vLLM, TensorRT-LLM). Blackwell-only features such as FP4 need libraries that implement them.
Is the B200 good value compared with the H100?
It costs 2.2× the H100 per month for about 2.3× the dense compute, so per unit of compute it is the cheaper of the two; per GB of memory it costs $14.94 against $15.61. If your job keeps it busy, the B200 is the lower cost per result.
Are the B200 and the H100 in stock?
8 of 12 B200 units were free at the last stock update; 14 of 64 H100 units were free at the last stock update (18 September 2026). Both are provisioned automatically, in under 10 minutes after payment.
Can I rent the B200 or the H100 without KYC?
Yes. Both are rented with an email address and paid from a prepaid balance in Bitcoin, Ether or USDT — $2,690 and $1,249 a month, dedicated, with no identity check and no card.
Other GPU comparisons
Both are in stock, by the month
Dedicated, single-tenant and live in under 10 minutes: the B200 at $2,690 or the H100 at $1,249 a month, paid in BTC, ETH or USDT with no KYC.