Should I choose B200, GB200, or GB300 for LLM inference, and what's the practical difference for my workload?

Teams comparing B200, GB200, and GB300 often read them as three tiers of the same product, from good to better to best. That framing leads to the wrong pick, because they are different units of compute at different points in the supply cycle, not three speeds of one chip. B200 is a single-GPU option for models that fit on one or a few GPUs, GB200 NVL72 is a rack-scale system for models that need a single high-bandwidth domain across many GPUs, and GB300 is the pre-order Blackwell Ultra refresh for the most memory-bound frontier inference, so the right choice is set by your model size and timeline, not by which name is newest. This guide maps each chip to the workload it fits and shows why availability decides two of the three.

They are different units of compute, not three speeds

The first correction is unit. B200 is an individual GPU you rent by the GPU-hour and combine into small deployments. GB200 NVL72 and GB300 NVL72 are rack-scale systems where dozens of GPUs share one interconnected domain. Comparing a single B200 to a GB200 rack is comparing one GPU to seventy-two, not a slow chip to a fast one.

That distinction drives the whole decision. B200 suits models that fit on one or a small number of GPUs, while GB200 NVL72 exists for models large enough that they must be sharded across many GPUs and benefit from a single NVLink domain instead of a networked cluster. If your model fits comfortably on one or two GPUs, a rack is capacity you pay for and cannot use. If your model must span many GPUs, stringing together individual B200s across nodes reintroduces the exact network bottleneck the rack was built to remove. Match the unit to the model first, and most of the choice is already made.

Where GB300 fits, and why availability matters

GB300 is the Blackwell Ultra refresh above GB200, aimed at the most memory-bound inference such as the largest models and longest contexts. But it is largely a pre-order product, which changes how you can choose it.

Availability is a selection criterion here, not a footnote. B200 and GB200 NVL72 are rentable now on clouds that carry them, while GB300 is largely pre-order, so choosing GB300 means planning around a delivery window rather than provisioning capacity you can benchmark today. For a workload you need to serve this quarter, that narrows the practical choice to B200 or GB200. For a forward-looking, memory-bound deployment where your timeline allows a reservation, GB300 is the option to plan toward, but as a dated reservation, not on-demand stock. Treat the newest chip as a roadmap decision, and the available ones as today's deployment decision.

Matching the chip to your workload

Use the frame below to map your model to the right unit. Availability is a column because it decides as much as performance.

Your workload	Best fit	Availability	Why
Model fits one or a few GPUs	B200	Limited, rentable now	Single-GPU unit, no rack overhead
Large model needing one NVLink domain	GB200 NVL72	Available now	Rack topology removes network bottleneck
Frontier, memory-bound, long-context	GB300 NVL72	Largely pre-order	Blackwell Ultra headroom, plan as reservation
Need capacity this quarter	B200 or GB200	Rentable now	GB300 timeline is a delivery window

The pattern is consistent: model size picks between a single GPU and a rack, and timeline picks between what is available now and what you reserve for later. A workload that fits a single B200 does not need a rack, and a frontier workload that will not fit today's chips is a GB300 reservation, not a B200 deployment.

Choosing among B200, GB200, and GB300 on GMI

Since the choice turns on model size and timeline, the practical step is using our platform, which carries all three so you can benchmark the available ones and reserve the next. We are an AI-native GPU and inference cloud that publishes dedicated NVIDIA GPU list pricing and lists B200, GB200 NVL72, and GB300 NVL72.

In our current published listings, B200 is listed at from $4.00 per GPU-hour under Limited Availability, GB200 NVL72 at from $8.00 per GPU-hour Available Now, and GB300 NVL72 as pre-order, so you can benchmark your model on B200 or GB200 today and open a GB300 reservation only if your workload needs the Blackwell Ultra headroom. Verify current rates and availability on our GPU infrastructure (https://www.gmicloud.ai/en/gpus) and pricing (https://www.gmicloud.ai/en/pricing), since Blackwell pricing and stock move quickly. Benchmark on the chip whose unit matches your model, single-GPU B200 for models that fit, GB200 NVL72 for models that need the rack, because that decides the real fit. When the workload is sustained production inference, our Prime Inference (https://www.gmicloud.ai/en/models/prime-inference) provides reserved GPU capacity with single-tenant isolation and warm serving on the chip you choose. Start on B200 or GB200 in our console (https://console.gmicloud.ai) and open a GB300 conversation with our sales team.

Pick the unit and the timeline, not the newest name

If you choose among B200, GB200, and GB300 by which sounds most advanced, you risk renting a rack for a model that fits one GPU, or pre-ordering frontier hardware your workload does not need. Decide on two axes instead: does your model fit a single GPU or need a full NVLink domain, and do you need capacity now or can you plan around a delivery window. B200 is the single-GPU answer, GB200 NVL72 the rack answer available today, and GB300 the memory-bound frontier reservation for later, so match the unit to the model and the timeline to your schedule rather than reaching for the newest chip on the list.