Rent NVIDIA RTX A6000 GPU
Launch NVIDIA RTX A6000 cloud capacity with 48GB VRAM for ai development, rendering, visualization, and inference. Lumino provides per-second billing, SSH access, a browser terminal, and public Docker image support.
Availability: NVIDIA RTX A6000 is part of the Lumino rental catalog; check current stock or create an Auto-rent request in the marketplace.
Check current RTX A6000 stock and pricing or create an Auto-rent request
Is NVIDIA RTX A6000 the right GPU for your workload?
48GB VRAM gives more room for quantized large models, LoRA fine-tuning, longer context, rendering, and concurrent inference than a 24GB GPU. 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: AI development, rendering, visualization, and inference.
Nearby alternatives to NVIDIA RTX A6000
- NVIDIA RTX A5000 — 24GB, Ampere, Supported by Lumino; check current RTX A5000 stock and pricing.
- NVIDIA RTX PRO 4000 Blackwell — 24GB, Blackwell, Supported by Lumino; check current RTX PRO 4000 stock and pricing.
- NVIDIA RTX 6000 Ada Generation — 48GB, Ada Lovelace, Supported by Lumino; check current RTX 6000 stock and pricing.
What fits in 48GB of VRAM: Proven memory for fine-tuning and experiments
- 30B-70B quantized models: INT4 and INT8 builds of large models fit in 48GB for inference and experimentation.
- LoRA fine-tuning: Adapter training with longer sequences and larger batches than 24GB GPUs allow.
- Parallel workloads: Run inference and background experiments side by side without memory pressure.
- On this card: On this card: GDDR6 memory, launched 2020, 768 GB/s bandwidth.
NVIDIA RTX A6000 specifications and rental details
| Hourly price | Check current marketplace pricing |
|---|---|
| GPU memory | 48GB VRAM |
| Architecture | Ampere |
| Fleet class | Workstation Pro |
| Memory bandwidth | 768 GB/s |
| FP16 performance | Up to 38.7 TFLOPS |
| Access | SSH, browser terminal, and Docker image support |
Where NVIDIA RTX A6000 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 768 GB/s.
How to rent NVIDIA RTX A6000
- Open the filtered marketplace result and confirm current stock and price.
- Select storage and a public Docker image for the workload.
- Start the rental, then connect over SSH or the browser terminal.
- Stop or terminate the pod when the job finishes and review any persistent-storage charge.
Open current RTX A6000 inventory
For serverless inference, compare Lumino hosted model APIs and review the developer documentation.
NVIDIA RTX A6000 rental FAQ
Can I rent NVIDIA RTX A6000 on Lumino AI?
Yes, Lumino AI maintains an explicit catalog entry for this GPU. NVIDIA RTX A6000 is part of the Lumino rental catalog; check current stock or create an Auto-rent request in the marketplace.
What is NVIDIA RTX A6000 best used for?
AI development, rendering, visualization, and inference. Actual fit depends on model precision, batch size, context length, framework overhead, and concurrent users.
How much does NVIDIA RTX A6000 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 48GB of VRAM?
48GB VRAM gives more room for quantized large models, LoRA fine-tuning, longer context, rendering, and concurrent inference than a 24GB GPU. This card ships GDDR6. Keep 20-30 percent headroom above the raw model weights for context and batch size.
NVIDIA RTX A6000 vs NVIDIA RTX A5000?
The NVIDIA RTX A5000 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 A6000?
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.