Distributed training
Test how model and training state are divided across four GPUs.
4 × A100 SXM rental
Four GPUs with 80 GB each for distributed workloads. Application support is required.
$5.728/ hour
Consider ASUS GX10 for LLMs
Choosing 4 × A100 SXM to run a language model? Compare your workload with ASUS Ascent GX10 rental: NVIDIA GB10 and 128 GB of unified CPU and GPU memory on one node.
Request one ASUS system for inference and RAG, or a pair for parallel workloads. Compare model and context memory, ARM64 support and the time needed for a trial run. GX10 unified memory and dedicated VRAM have different trade-offs.
Match ASUS GX10 to your modelASUS Ascent GX10
128 GB unified memory · NVIDIA GB10 · one system or a pair. Availability and software are agreed for your workload.
Offer ends in—d—h—m—s
Workloads for this GPU configuration
Multi-device models
Evaluate model-parallel support and each A100’s memory separately.
Independent experiment batches
Schedule experiments across GPUs when each job fits within 80 GB.
Software compatibility
- Memory is per card: 4 × 80 GB HBM2e. It is not automatically pooled.
- A shared model across four 80 GB devices requires distributed application support.
- Confirm interconnect topology, CPU, RAM and storage requirements for your workload.
Rent 4 × A100 SXM
Provide your model, software environment and rental period. We will confirm the rate, availability and connection method before the rental starts.
$5.728/ hour
About this configuration
Is memory pooled across all GPUs?
Memory is per card: 4 × 80 GB HBM2e. It is not automatically pooled.
What should I prepare for four A100 GPUs?
Provide the model, framework version, parallelism strategy, batch size and launch command. Include dataset size and cross-GPU communication needs: GPU count does not describe the whole server.
How do I request this configuration?
This configuration is open for rental requests. Share your workload, preferred dates and duration. Hardware availability, pricing and access dates are confirmed individually; a request does not create a confirmed booking.
