GB200 NVL72 / GB200 vs GB300
GB200 vs GB300 NVL72
Same rack shape, one GPU generation apart. Here's what changed, and when GB200 is the smarter rent.
Side by side
| Per GPU | GB200 NVL72 | GB300 NVL72 |
|---|---|---|
| GPU | Blackwell | Blackwell Ultra |
| HBM3e | 192 GB | 288 GB |
| FP4 compute | 1x | ~1.5x |
| Back-end network | 400 Gb/s | 800 Gb/s |
| GPUs per NVLink domain | 72 | 72 |
| In service since | Early 2025 | Aug 2025 |
Per-GPU figures from Microsoft's ND GB200 v6 and ND GB300 v6 documentation (GB200, GB300). Service dates from CoreWeave's GB200 launch and the GB300 launches listed on gb300nvl72.com.
When GB200 is the better rent
- Your model fits. If weights plus KV cache fit comfortably in 192 GB per GPU, GB300's extra memory buys you little.
- You need racks soon. GB200 has a bigger installed base and more racks rolling off first contracts.
- You're training on one or a few racks. Most traffic stays on NVLink, so the slower back-end network matters less.
- Your budget is fixed. An older generation is usually the easier rate to negotiate. Ask for both and compare.
When to pay up for GB300
- Long-context or reasoning inference where the KV cache is the limit.
- Multi-rack training where traffic between racks is the bottleneck.
- A multi-year term, where the newer part stays useful for longer.
Our form lets you ask for both in one request. For GB300 detail, see gb300nvl72.com.
Questions
Is GB300 worth it over GB200?
If you're memory-bound (large models, long contexts, big batches) usually yes. If your model fits in 192 GB per GPU and you need racks soon, GB200 is often the better deal. Ask for both.
Can GB200 and GB300 racks share a cluster?
They use the same rack design, but mixing generations in one training job is rarely a good idea. Treat them as separate pools.
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