Solved NVIDIA DGX Spark (GB10)

It depends on the model, context length, output length, batching, quantization and what latency you consider acceptable.

A 7B model and a 30B dense model can differ massively even on the same GB10.

Give us the model plus average prompt/output sizes and target requests per minute. Then we can load-test or estimate it.

Without those numbers, any 'users per GB10' figure would be marketing rather than capacity planning.

What's the difference between Managed GPU and normal GPU rental?

With normal rental, you operate the machine. With Managed GPU, AxForge operates the AI stack for you.

Managed GPU includes scoping the machine, runtime, model deployment, inference server, networking and endpoint.

It is the option for someone who wants dedicated hardware but does not want to manage CUDA, drivers, vLLM and the serving environment themselves.

Can I rent a GB10 for only a few hours?

Yes. AxForge offers hourly access to dedicated DGX Spark machines.

You can use on-demand capacity or reserve a start time, depending on availability.