GPU compute for robotics & physical AI
Validate simulation, perception and robot learning with a scoped GPU pilot before scaling.
Who is this for?
For robotics startups, research laboratories, industrial automation teams and simulation developers who need repeatable experiments without buying a dedicated GPU server.
Typical workloads
- Simulation and synthetic data: sensor rendering, scene variation and labelled images.
- Perception and robot learning: vision model fine-tuning, imitation learning and policy evaluation.
- Batch experiments: compare policies across scenarios, then validate separately on physical hardware.
Recommended GPUs to evaluate
- RTX simulation: shortlist L40S or RTX PRO 6000 Server; confirm the exact Isaac Sim version, driver, renderer and GPU support before quoting.
- Learning workloads: evaluate A100 or H100; consider H200 when model and activation memory require more headroom. These are not substitutes for RTX rendering requirements.
Final selection depends on your software, memory budget and pilot results. Capacity and the full configuration are confirmed in the quote.
NVIDIA Isaac Sim requirements ↗How many GPUs should I start with?
Start with one compatible RTX GPU for a small simulation scene. For a separate learning job, test one training GPU first; compare two to four only when the framework and workload can use them. This is a sizing starting point, not a performance guarantee.
How does the pilot work?
Scope: choose one scene or dataset, the software version and a target such as simulation steps per second or perception accuracy.
Agree: review GPU compatibility, storage, region, infrastructure provider, pilot duration and the AUD quote. No charge before you accept the quote.
Run: benchmark the agreed sample, record peak memory, throughput and output quality, then review whether to stop, adjust or scale.
Agree the scope, duration, acceptance criteria and price in advance. A pilot is not a free-trial offer. No charge before you accept the quote; the infrastructure provider is disclosed before activation.
How do I request a quote?
Include your simulator and version, scene size, sensors, learning framework, dataset size, preferred region and deadline. Describe requirements rather than uploading proprietary datasets or credentials.
Submit the enquiry form. Arvica reviews compatibility and capacity, then provides an AUD quote for you to accept before activation. English and Chinese assistance is available during Australia/APAC business hours.
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