Rent NVIDIA RTX A4000 GPU

Launch NVIDIA RTX A4000 cloud capacity with 16GB VRAM for inference, media, rendering, and virtual workstations. Lumino provides per-second billing, SSH access, a browser terminal, and public Docker image support.

Availability: NVIDIA RTX A4000 is part of the Lumino rental catalog; check current stock or create an Auto-rent request in the marketplace.

Check current RTX A4000 stock and pricing or create an Auto-rent request

What fits in 16GB of VRAM: Proven memory for fine-tuning and experiments

  • Compact models: Small language models, embeddings, and classifiers fit in 16GB.
  • Prototypes: CUDA development, testing, and measured trial workloads before scaling up.
  • On this card: On this card: GDDR6 memory, launched 2021, 448 GB/s bandwidth.

Is NVIDIA RTX A4000 the right GPU for your workload?

16GB VRAM is best for compact models, prototypes, CUDA development, image workflows, and jobs whose memory requirement has been measured before launch. This card ships GDDR6.

Choose this workstation GPU for mixed AI, visualization, rendering, CAD, or virtual-workstation workloads that benefit from professional drivers and larger memory configurations.

Ampere is the mature workhorse: broad CUDA and framework support, and on A100-class silicon, MIG slices that split one GPU into isolated fractional rentals.

Typical workloads: Inference, media, rendering, and virtual workstations.

NVIDIA RTX A4000 specifications and rental details

Hourly priceCheck current marketplace pricing
GPU memory16GB VRAM
ArchitectureAmpere
Fleet classWorkstation Pro
Memory bandwidth448 GB/s
FP16 performanceUp to 19.2 TFLOPS
AccessSSH, browser terminal, and Docker image support

Where NVIDIA RTX A4000 bottlenecks

Ampere bottlenecks are usually memory capacity and host-to-device transfer on large batches; MIG slicing helps only on supported A100-class silicon. Memory bandwidth on record is 448 GB/s.

Nearby alternatives to NVIDIA RTX A4000

Compare the complete Lumino GPU fleet

How to rent NVIDIA RTX A4000

  1. Open the filtered marketplace result and confirm current stock and price.
  2. Select storage and a public Docker image for the workload.
  3. Start the rental, then connect over SSH or the browser terminal.
  4. Stop or terminate the pod when the job finishes and review any persistent-storage charge.

Open current RTX A4000 inventory

For serverless inference, compare Lumino hosted model APIs and review the developer documentation.

NVIDIA RTX A4000 rental FAQ

Can I rent NVIDIA RTX A4000 on Lumino AI?

Yes, Lumino AI maintains an explicit catalog entry for this GPU. NVIDIA RTX A4000 is part of the Lumino rental catalog; check current stock or create an Auto-rent request in the marketplace.

What is NVIDIA RTX A4000 best used for?

Inference, media, rendering, and virtual workstations. Actual fit depends on model precision, batch size, context length, framework overhead, and concurrent users.

How much does NVIDIA RTX A4000 rental cost in India?

The hourly rate is listed live in the marketplace with per-second INR billing. Total job cost is rate times runtime plus any persistent storage.

What fits in 16GB of VRAM?

16GB VRAM is best for compact models, prototypes, CUDA development, image workflows, and jobs whose memory requirement has been measured before launch. This card ships GDDR6. Keep 20-30 percent headroom above the raw model weights for context and batch size.

NVIDIA RTX A4000 vs NVIDIA RTX 6000 Ada Generation?

The NVIDIA RTX 6000 Ada Generation is the closest rentable alternative by category and memory. Pick by VRAM fit first, then hourly rate.

Can I split this GPU into smaller slices on NVIDIA RTX A4000?

A100-class Ampere silicon supports MIG slices: isolated fractional GPUs with their own memory and compute, rentable separately when a full card is unnecessary.

Is Ampere still worth renting?

Yes for value: mature CUDA support across every framework, and on 80GB cards, room for 70B-class inference and LoRA work at below-flagship hourly rates.

Does the rental include SSH and Docker?

Yes. Lumino supports SSH, a browser terminal, and public Docker images for supported CUDA workloads.