Question 1

What AI models can run on B200?

Accepted Answer

The B200 (192 GB VRAM) can run models including Llama-2-13b, MediPhi-MedWiki, Llama-2-7b, Llama-2-70b, intent-aware-lfqa-qwen3-4b-intent-implicit and more — 10 compatible models indexed so far. Compatible models are determined by whether the model's memory footprint fits within the GPU's 192 GB VRAM, potentially using quantization (Q8, Q6, or Q4) to reduce memory usage.

Question 2

What is the cheapest cloud option for B200?

Accepted Answer

The cheapest on-demand option for the B200 is Lambda at $6.99/hr (gpu_1x_b200_sxm6). We track pricing across 33 providers to help you find the best deal.

Question 3

Is B200 good for fine-tuning?

Accepted Answer

Yes, the B200 is excellent for fine-tuning. With 192 GB of VRAM, it can handle full fine-tuning of models up to ~30B parameters and LoRA/QLoRA fine-tuning of much larger models. It's a top-tier choice for training workloads.

Question 4

How much VRAM does B200 have?

Accepted Answer

The B200 has 192 GB of VRAM (HBM3e). It also offers 8000 GB/s memory bandwidth, 2,250 TFLOPS of FP16 compute, FP8 support for efficient inference.

Question 5

What quantization formats work on B200?

Accepted Answer

The B200 supports the following quantization formats: FP16 (full precision), FP8, Q8 (8-bit), Q6 (6-bit), Q4 (4-bit). FP16 works for models up to ~40B parameters. FP8 halves memory vs FP16 with minimal quality loss. Q4 quantization lets models up to ~652B parameters (by VRAM estimate) fit on the B200.

Provider	On-demand	Spot	Actions
Lambda	$6.990/hr	—	—
RunPod	$7.990/hr	—	Rent Get $5–$500 free
Nebius	$8.500/hr	$0.990/hr	—

B200

Specifications

Cloud pricing

Compatible models

Compare this GPU

Frequently asked questions

VRAM	192 GB
Memory type	HBM3e
Bandwidth	8000 GB/s
FP16 TFLOPS	2,250
FP8 support	Yes