B300 vs B200: which Blackwell node, and why the right one lowers your TCO

FlexiCloud runs two Blackwell nodes: the B300 and the B200. The question people ask is "which is better?" But that is the wrong question. They are not better and worse; they are sized for different jobs. And which one you pick is the single biggest lever you have on what the compute actually costs you. So this is a comparison, and it is a total-cost-of-ownership argument, because the two are the same argument.

The difference that matters is memory

Both are 8-GPU SXM nodes with NVLink across the node, on the same six-month terms, in the same regions (India, the EU and the US). The hardware difference that drives everything else is memory per GPU:

• B300 (Blackwell Ultra): 288 GB HBM3e per GPU, 2.3 TB per node. From $4.50 per GPU-hour.
• B200 (Blackwell): 192 GB HBM3e per GPU, 1.5 TB per node. From $3.75 per GPU-hour.

The B200 is roughly 17% cheaper per GPU-hour. The B300 carries 50% more memory. Everything below is about when each of those numbers is the one that decides your bill.

Why memory, not the hourly rate, drives TCO

It is tempting to compare the two on the per-GPU-hour rate alone and stop there. That is the mistake. Memory decides how many GPUs and how many nodes a workload needs, and that count, not the sticker rate, is what dominates total cost. A model that fits in one GPU's memory is far cheaper to run than the same model split across two, because splitting adds GPUs, adds interconnect traffic, and adds the coordination overhead that keeps expensive chips waiting. (We went through that memory arithmetic in will your model fit? and the communication side in the fabric that makes eight GPUs act as one.)

So the real comparison is not "$4.50 vs $3.75". It is "how many GPU-hours does your workload take on each", and memory is what sets that.

When the B200 is the lower-TCO choice

For the large majority of workloads, the B200 is the right answer and the cheaper one. If your model, its KV cache and, for training, its optimizer state fit comfortably in 192 GB per GPU, the B200 does exactly the same job as the B300 for 17% less per hour. Paying for 288 GB you do not use is not "more value", it is a worse TCO. Most fine-tuning, most inference, and a great deal of training sits here. When the work fits, the B200 wins on cost, plainly.

When the B300 earns its premium

The B300's extra memory is not a luxury when you are memory-bound; it is what makes the cheaper node, counter-intuitively, the more expensive one. If a model needs more than 192 GB per GPU, the B200 forces you to split it across more GPUs or more nodes. Now you are renting more hardware, paying for more interconnect, and living with more parallelism overhead. The B300's 288 GB can let you do on one GPU, or one node, what the B200 would need two of, and fewer nodes at a higher rate can be a lower total than more nodes at a lower rate. The largest models, the longest context windows, and memory-bound training are where the B300 is the lower-TCO choice, not despite its price but because of its memory.

The bigger TCO picture: rented bare metal vs owning

There is a second, larger TCO argument underneath the model choice. When you rent a dedicated node from us, your total cost is the rate times the hours, and that is the whole bill. There is no capital outlay, no depreciation on a fast-obsoleting asset, no power and cooling, no datacentre space, and no idle cost when a project pauses. Owning an eight-way Blackwell box carries all of those whether the GPUs are busy or not, and they usually dwarf the compute itself. We walk through that trade-off in rent, buy or API. The short version: for anything short of years of sustained, near-full utilisation, rented bare metal is the lower TCO, and picking B200 or B300 correctly is how you minimise it further.

How to choose in practice

Two questions settle it:

• Does your workload fit in 192 GB per GPU? If yes, take the B200 and pay less. If no, the B300's headroom will likely cost you less overall by needing fewer GPUs.
• How many GPU-hours will the job take? That, times the rate, is the real number, and it is worth estimating before you commit. Our cost breakdown shows the arithmetic.

You do not have to work this out alone. Tell us the model, the method and the deadline, and we will tell you straight which node is the lower total cost for your workload, even when that means steering you to the cheaper B200. Compare the two on the pricing page, read the details for the B300 or the B200, or talk to an engineer.