RTX A6000 Hosting | Dedicated 48GB RTX A6000 Servers

Q: What is Quadro RTX A6000 Hosting best for?

The Quadro RTX A6000 Hosting is perfect for Deep learning and 3D rendering. You get a performance boost with NVIDIA DLSS (Deep Learning Super Sampling).

Q: Can I add more resources to my RTX A6000 server?

Yes, you can add more A6000 card resources or other hardware configurations, such as CPU, RAM, and bandwidth, to your RTX A6000 server. The additional GPU A6000 price is $349/m.

Q: Is A6000 better than 3090?

While the Nvidia RTX A6000 has a slightly better GPU configuration than the GeForce RTX 3090, it uses slower memory. It has 768 GB/s of memory bandwidth, which is 18% lower than consumer cards (936 GB/s), so it won't beat the 3090 in games. It performs better in professional workloads that require a lot of memory.

Q: Why is RTX A6000 hosting server best for machine learning?

New Tensor Float 32 (TF32) precision provides up to 5X the training throughput over the previous generation to accelerate AI and data science model training without requiring any code changes. Hardware support for structural sparsity doubles the throughput for inferencing. Tensor cores also bring AI to graphics with capabilities like DLSS, AI denoising, and enhanced editing for select applications.

Q: Do you provide a RTX A6000 trial server?

You can request a test server if you would like to test if the chosen configurations of the dedicated server can support running your software. To test the internet speed to resources hosted on our servers, you can ping our data center IP without having to wait for the test server.

Q: Is NVIDIA A6000 good for gaming?

Although the RTX A6000 performs relatively well in all aspects, it was not created specifically for gaming. For gamers, a GeForce GTX 10 series or 20 series graphics card would be more appropriate.

Q: RTX A6000 VS Nvidia A40, which is better?

The RTX A6000 and Nvidia A40 are comparable in performance. Both of them are the best candidates for high-performance computing, large AI computing scenarios, and high-precision enterprise-class computing.

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Quadro RTX A6000 GPU Hosting Pricing

The GPU dedicated server with Quadro RTX A6000 is equipped with dual Silver 5314 CPU and 258GB RAM, delivering high performance for your Deep Learning projects.

Enterprise Dedicated GPU Server - RTX A6000

RTX A6000 delivers everything for designers, engineers, scientists, and artists need to meet the most graphics and compute-intensive workflows.

GPU: RTX A6000
CPU: 2 x 18-Core E5-2697v4
Memory: 256GB RAM
Disk: 240GB SSD+2TB NVMe+8TB SATA
Bandwidth: 100Mbps Unmetered
GPU Memory: 48 GB GDDR6

IP: 1 Dedicated IPv4
Location: USA

1mo3mo12mo24mo

$ 409.00/mo

Enterprise Multi-GPU Dedicated Server - 3xRTX A6000

GPU: 3 x RTX A6000
CPU: 2 x 18-Core E5-2697v4
Memory: 256GB RAM
Disk: 240GB SSD+2TB NVMe+8TB SATA
Bandwidth: 1000Mbps Unmetered
GPU Memory: 48 GB GDDR6

IP: 1 Dedicated IPv4
Location: USA

1mo3mo12mo24mo

$ 899.00/mo

Enterprise Multi-GPU Dedicated Server - 4xRTX A6000

GPU: 4 x RTX A6000
CPU: 2 x 22-Core E5-2699v4
Memory: 512GB RAM
Disk: 240GB SSD+4TB NVMe+16TB SATA
Bandwidth: 1000Mbps Unmetered
NVLink: 2xNVLink
GPU Memory: 48 GB GDDR6

IP: 1 Dedicated IPv4
Location: USA

1mo3mo12mo24mo

$ 1199.00/mo

RTX A6000 WORKLOAD OPTIONS

Choose the Right RTX A6000 Server Configuration

Compare RTX A6000 rental options with 48GB of dedicated GPU memory for professional AI, visualization, rendering, and compute-intensive workloads.

RTX A6000 Server for AI & LLMs

An RTX A6000 server is suitable for LLM inference, fine-tuning, computer vision, AI agents, and workloads that benefit from 48GB of dedicated GPU memory.

RTX A6000 Hosting for Rendering

Use RTX A6000 hosting for 3D rendering, animation, architectural visualization, video workflows, and GPU-accelerated creative projects.

RTX A6000 Dedicated Server

An RTX A6000 dedicated server supports parallel AI, rendering, and inference workloads. RTX A6000 rental provides dedicated multi-GPU capacity for larger production deployments with predictable monthly billing.

Nvidia Quadro RTX A6000 GPU Benchmarks on LLM Inference

The following data reflects the inference performance benchmarks we conducted for various open-source LLMs, utilizing Ollama and vLLM on our Quadro RTX A6000 servers.

Nvidia Quadro RTX A6000 GPU Benchmark with Ollama

Models	deepseek-r1	deepseek-r1	deepseek-r1	llama2	llama2	llama3	llama3.3	qwen	qwen	qwen2.5	qwen2.5	gemma2	llava	qwq	phi4
Parameters	14b	32b	70b	13b	70b	70b	70b	32b	72b	14b	32b	27b	34b	32b	14b
Size(GB)	9GB	20GB	43GB	7.4GB	39GB	40GB	43GB	18GB	41GB	9GB	20GB	16GB	19GB	20GB	9.1GB
Quantization	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4
Running on	Ollama0.5.11	Ollama0.5.11	Ollama0.5.11	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4	Ollama0.5.4
Downloading Speed(mb/s)	11	11	11	11	11	11	11	11	11	11	11	11	11	11	11
CPU Rate	3%	3%	3%	3%	5%	3%	3%	3%	3%	3%	3%	3%		3%	3%
RAM Rate	4%	4%	4%	3%	3%	3%	3%	4%	3%	3%	4%	3%	4%	4%	4%
GPU vRAM	78%	68%	90%	30%	85%	88%	91%	42%	91%	22%	67%	40%	85%	91%	70%
GPU UTL	86%	92%	96%	87%	96%	94%	94%	89%	94%	83%	89%	84%	68%	89%	83%
Eval Rate(tokens/s)	48.40	26.23	13.65	63.63	15.28	14.67	13.56	27.96	14.51	50.32	26.08	31.59	28.67	25.57	52.62

Nvidia Quadro RTX A6000 GPU Benchmark with vLLM (1: 50 Concurrent Requests)

Models	Qwen2.5-7B-Instruct	Qwen2.5-14B-Instruct	Llama-3.1-8B-Instruct	DeepSeek-R1-Distill-Llama-8B	DeepSeek-R1-Distill-Qwen-14B
Quantization	16	16	16	16	16
Size（GB）	15	28	15	15	28
Backend/Platform	vLLM	vLLM	vLLM	vLLM	vLLM
Request Numbers	50	50	50	50	50
Benchmark Duration(s)	17.81	36.25	18.26	19.37	31.04
Total Input Tokens	5000	5000	5000	5000	5000
Total Generated Tokens	23817	25213	22247	26839	17572
Request (req/s)	2.81	1.38	2.74	2.58	1.61
Input (tokens/s)	280.74	137.93	273.89	258.16	161.07
Output (tokens/s)	1337.24	695.51	1218.63	1385.77	566.08
Total Throughput (tokens/s)	1617.98	833.44	1492.52	1643.93	727.15
Median TTFT(ms)	583.54	1095.08	593.26	652.56	474.60
P99 TTFT(ms)	761.02	1407.86	810.46	857.21	637.96
Median TPOT(ms)	28.67	58.59	29.40	31.15	51.18
P99 TPOT(ms)	160.33	63.10	39.80	38.20	64.46
Median Eval Rate(tokens/s)	34.88	17.07	34.01	32.10	19.54
P99 Eval Rate(tokens/s)	6.23	15.85	25.13	26.18	15.51

Nvidia Quadro RTX A6000 GPU Benchmark with vLLM (2: 100 Concurrent Requests)

Models	Qwen2.5-7B-Instruct	Qwen2.5-14B-Instruct	Llama-3.1-8B-Instruct	DeepSeek-R1-Distill-Llama-8B	DeepSeek-R1-Distill-Qwen-14B
Quantization	16	16	16	16	16
Size（GB）	15	28	15	15	28
Backend/Platform	vLLM	vLLM	vLLM	vLLM	vLLM
Request Numbers	50	50	50	50	50
Benchmark Duration(s)	22.41	49.77	21.52	22.51	37.09
Total Input Tokens	10000	10000	10000	10000	10000
Total Generated Tokens	49662	51632	47223	54501	38003
Request (req/s)	4.46	2.01	4.65	4.44	2.70
Input (tokens/s)	446.22	200.93	464.6	444.22	269.61
Output (tokens/s)	2216.02	1037.44	2193.97	2421.04	1024.60
Total Throughput (tokens/s)	2662.24	1238.37	2658.57	2865.26	1294.21
Median TTFT(ms)	414.18	804.91	543.01	585.56	1673.75
P99 TTFT(ms)	950.56	1688.46	1015.96	1086.52	2830.12
Median TPOT(ms)	36.74	69.58	34.86	36.42	59.22
P99 TPOT(ms)	232.43	80.00	55.98	47.82	126.96
Median Eval Rate(tokens/s)	27.22	14.37	29.68	27.46	16.89
P99 Eval Rate(tokens/s)	4.30	12.5	17.86	20.91	7.87

4×Nvidia Quadro RTX A6000 GPU vLLM Benchmark for 50 Concurrent Requests

Models	Qwen/Qwen2.5-VL-72B-Instruct	meta-llama/Meta-Llama-3-70B-Instruct	meta-llama/Llama-3.1-70B	deepseek-ai/DeepSeek-R1-Distill-Llama-70B	Qwen/Qwen3-32B
Quantization	16	16	16	16	16
Size（GB）	137	132	132	132	65
Backend/Platform	vLLM	vLLM	vLLM	vLLM	vLLM
Tensor Parallelism	4	4	4	4	4
Request Numbers	50	50	50	50	50
Benchmark Duration(s)	68.59	63.96	65.50	66.46	33.11
Total Input Tokens	5000	5000	5000	5000	5000
Total Generated Tokens	25834	22252	24527	25994	22406
Request (req/s)	0.73	0.78	0.76	0.75	1.51
Input (tokens/s)	72.89	78.17	76.34	75.22	151.02
Output (tokens/s)	376.62	347.93	374.45	391.10	676.72
Total Throughput (tokens/s)	449.51	426.10	450.79	466.32	827.74
Median TTFT (ms)	4134.85	4028.61	3945.48	4055.27	1958.54
P99 TTFT (ms)	5269.88	5126.21	5019.25	5157.44	2495.06
Median TPOT (ms)	107.41	102.25	102.61	104.10	52.33
P99 TPOT (ms)	113.69	1743.43	1900.50	136.96	96.08
Median Eval Rate (tokens/s)	9.31	9.78	9.74	9.61	19.10
P99 Eval Rate (tokens/s)	8.79	0.57	0.56	7.30	10.41

Specifications of Nvidia RTX A6000 Ampere

The NVIDIA RTX A6000 Ampere is a high-performance professional GPU built for dedicated hosting that demands advanced AI acceleration, photorealistic rendering, and massive data-set compute performance.

Basic Specifications

GPU Microarchitecture

Ampere

Memory

48GB GDDR6 with error-correcting code (ECC)

Tensor Cores

336

CUDA Cores

10,752

FP16 (half)

38.71 TFLOPS (1:1)

FP32 (float)

38.71 TFLOPS

FP64 (double)

1.21 TFLOPS

Compute Capability

8.6

Technology Support

vGPU software support

NVIDIA vPC/vApps, NVIDIA RTX, Virtual Workstation, NVIDIA Virtual, Compute Server

Encode/decode engines

1x encode, 2x decode (+AV1 decode)

VR ready

Yes

vGPU profiles supported

1 GB, 2 GB, 3 GB, 4 GB, 6 GB, 8 GB,12 GB, 16 GB, 24 GB, 48 GB

Graphics APIs

DirectX 12.0710, Shader Model 5.1710,OpenGL 4.6811, Vulkan 1.1811

Compute APIs

CUDA, DirectCompute, OpenCL™

Other Specifications

TMUs

336

ROPs

112

TDP

300W

Memory Bus Width

384-bit

Memory Clock Speed

2000 MHz

Memory Bandwidth

768 GB/s

System Interface

PPCI Express 4.0 x16

GPU Clock speed

1410 MHz

Compare Related GPU Server Options

Compare other 48GB GPU server options, explore multi-GPU configurations, review GPU rendering servers, or browse AI server plans.

Features of Nvidia Quadro RTX A6000

Hosted GPU servers contain A6000 graphics cards deliver the cutting-edge performance and features.

CUDA cores based on NVIDIA's Ampere architecture

Dual-speed processing of single-precision floating-point (FP32) operations and improved power efficiency provide significant performance improvements for graphics and simulation workflows on the desktop, such as complex 3D computer-aided design (CAD) and computer-aided engineering (CAE).

Second Generation RT Cores

The second-generation RT core delivers up to 2x higher throughput than the previous generation and the ability to run ray tracing with shading or denoising simultaneously, providing tremendous speed for workloads such as photorealistic rendering of cinematic content, architectural design evaluation, and virtual prototyping of product designs. This technology also speeds up the rendering of ray-traced motion blur for faster and more accurate visuals.

Third Generation Tensor Core

The new Tensor Floating 32 (TF32) precision provides 5x higher training throughput than the previous generation to accelerate AI and data science model training without any code changes. Hardware support for structural sparsity doubles inference throughput. Tensor Cores also bring AI to the graphics domain with features such as DLSS, AI denoising, and application-specific enhanced editing.

48GB DDR6 Memory

Ultra-fast GDDR6 memory, scalable to 96GB via NVLink, provides data scientists, engineers and creative professionals with the large memory needed to handle large data sets and workloads such as data science and simulation.

Virtualization Ready

Support for NVIDIA virtual GPU (vGPU) software enables an RTX A6000-powered remote dedicated server environment to support virtual workstation and graphics-intensive workloads. Learn when an NVIDIA vGPU server model is suitable for remote visualization, virtual desktops, design workflows, and GPU resource planning.

PCI Express Gen 4

Support for PCI Express Gen 4 provides twice the bandwidth of PCIe Gen 3, increasing CPU memory data transfer speeds for data-intensive tasks such as artificial intelligence and data science.

What is Nvidia Quadro RTX A6000 GPU Server Used for?

Renting a dedicated server with A6000 GPU and quickly commit to projects in these scenarios.

Server RTX A6000 for AI & Deep Learning

The RTX A6000 is built on the 8 nm process, and based on the GA102 graphics processor, the card supports DirectX 12 Ultimate. It features 10752 shading units, 336 texture mapping units, and 112 ROPs. It also includes 336 tensor cores, which help improve the speed of machine-learning applications

RTX A6000 is ECC supportive, and best for the enterprise level application or any large-scale deep learning task where data accuracy is critical.

Server RTX A6000 for Rendering Large Scenes

The Nvidia RTX A6000 is ideal for rendering large scenes with its 48GB of VRAM and NVLink support. Nearly doubling the performance of the previous generation Quadros, it represents a major upgrade in every aspect. If you work with especially high-resolution renders and have scenes with a large amout of polygons, materials or effects, having 48GB of VRAM can be the difference between a smooth workflow and one plagued with 'Your GPU memory is full' errors.

What Can Be Run on Quadro RTX A6000 Hosting Server?

Here is the most running apps on A6000 GPU servers

Alternatives to GPU server with Quadro RTX A6000

Get the ultimate AI experience with A6000 GPU dedicated server.

GeForce RTX 3060 Ti Hosting

For professionals. It delivers real-time ray tracing, AI accelerated computing, and high-performance graphics to desktops.

GeForce RTX 4090 Hosting

Achieve an excellent balance between function, performance, and reliability. Assist designers, engineers, and artists to realize their visions.

RTX A5000 Hosting

Achieve an excellent balance between function, performance, and reliability. Assist designers, engineers, and artists to realize their visions.

Compare popular GPU cards by performance, memory, and use cases to help you choose the right GPU for your workload.

RTX A6000 vs RTX 5090

Explore the RTX A6000 vs. RTX 5090, with the RTX 5090 offering 3x AI boost and the A6000 providing stability for large models.

Read More >

RTX A5000 vs RTX A6000 Server Options

Compare RTX A5000 and RTX A6000 dedicated GPU server options by GPU memory, rendering requirements, AI workloads, and current plan availability.

View RTX A5000 Plans →

NVIDIA A100 and RTX A6000 server options

NVIDIA A100 vs RTX A6000 Server Options

Compare A100 and RTX A6000 server options for AI training, LLM inference, HPC, and workloads that require large dedicated GPU memory.

View A100 Plans →

RTX 4090 vs RTX A6000 Server Options

Compare RTX 4090 and RTX A6000 dedicated GPU server options for rendering, AI development, graphics workloads, and different VRAM requirements.

View RTX 4090 Plans →

FAQ of Quadro RTX A6000 GPU Hosting

Answers to more questions about the RTX A6000 GPU server hosting service can be found here

What is Nvidia Quadro RTX A6000 GPU dedicated Hosting?

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The RTX A6000 Hosting is a dedicated server with dual Silver CPU, 256 GB RAM and SSD disks, and you can enjoy a free tech support from engineers ready to troubleshoot your hardware, operating system, and machine learning software.

What is Quadro RTX A6000 Hosting best for?

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Can I add more resources to my RTX A6000 server?

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Is A6000 better than 3090?

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Why is RTX A6000 hosting server best for machine learning?

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Do you provide a RTX A6000 trial server?

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Is NVIDIA A6000 good for gaming?

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RTX A6000 VS Nvidia A40, which is better?

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RTX A6000 Hosting: Dedicated 48GB GPU Servers

Quadro RTX A6000 GPU Hosting Pricing