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A6000 vs A4000

Explore a head to head comparison of specifications, performance, and pricing.

A6000

The NVIDIA A6000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$2.42/hr
GPU VRAM48 GB
Cloud Availability6 clouds
System Memory512 GB
CPU Cores252
Storage2.6 TB

A4000

The NVIDIA A4000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$1.17/hr
GPU VRAM16 GB
Cloud Availability2 clouds
System Memory215 GB
CPU Cores56
Storage1.3 TB

A6000 vs A4000: Which Should You Choose?

The A6000 offers 48 GB of VRAM — 3× the 16 GB on the A4000 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the A6000 delivers 38.71 TFLOPS versus 19.17 TFLOPS on the A4000 — 2× faster for mixed-precision training and inference. Memory bandwidth favors the A6000 at 0.77 TB/s compared to 0.45 TB/s on the A4000, which directly impacts inference latency for memory-bandwidth-bound models. On Shadeform, the A4000 starts from $0.15/hr versus $0.49/hr for the A6000 — 227% more expensive — reflecting the performance premium. The A6000 is available across 6 cloud providers on Shadeform compared to 2 for the A4000, giving more options for region and pricing flexibility.

A6000 — Best Use Cases

  • General-purpose deep learning training
  • Fine-tuning models up to 13B parameters
  • AI inference at moderate throughput
  • Computer vision and NLP workloads

Choose A6000 when:

  • You need 48 GB+ VRAM for large models or long context windows
  • Maximum performance justifies the higher cost
  • You are training large models or running high-throughput inference
  • You need flexibility across multiple cloud providers or regions

A4000 — Best Use Cases

  • General-purpose deep learning training
  • Fine-tuning models up to 13B parameters
  • AI inference at moderate throughput
  • Computer vision and NLP workloads

Choose A4000 when:

  • 16 GB VRAM is sufficient for your workload
  • Cost efficiency is your primary concern
  • Your workload does not require peak FP16 throughput
  • Your preferred provider already has availability

See how the A6000 & A4000 compare

Compare detailed hardware specifications and average pricing for the A6000 and A4000.

Compare Hardware Specifications

A6000A4000
GPU Type
A6000
A4000
VRAM per GPU
48 GB
16 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Ampere
Ampere
Interconnect
PCIe Gen4
PCIe Gen4
Memory Bandwidth
768 GB/s
448 GB/s
FP16 TFLOPS
38.71 TFLOPS (1:1)
19.17 TFLOPS (1:1)
CUDA Cores
10752
6144
Tensor Cores
336 (3rd Gen)
192 (3rd Gen)
RT Cores
84 (2nd Gen)
48 (2nd Gen)
Base Clock
1410 MHz
735 MHz
Boost Clock
1800 MHz
1695 MHz
TDP
300W
140W
Process Node
TSMC 8nm
TSMC 8nm
Data Formats
INT8, BF16, FP16, TF32, FP32
INT8, BF16, FP16, TF32, FP32

Compare Average On-Demand Pricing

A6000A4000
1 GPU
$0.94 /hr
$0.47 /hr
2 GPUs
$1.89 /hr
$0.95 /hr
4 GPUs
$3.77 /hr
$1.90 /hr
8 GPUs
$4.16 /hr
$1.20 /hr

Frequently Asked Questions: A6000 vs A4000

The main differences are VRAM (48 GB vs 16 GB), FP16 throughput (38.71 vs 19.17 TFLOPS).

The A6000 is generally better for large language model training due to its higher throughput and 48 GB of VRAM, which allows fitting larger models or larger batch sizes in a single pass. For smaller models or fine-tuning tasks where cost matters more, both GPUs can be effective.

On Shadeform, the A4000 is available from $0.15/hr. The A6000 starts from $0.49/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.

The A6000 has more VRAM at 48 GB, compared to 16 GB on the A4000. Higher VRAM allows you to run larger models without quantization, use longer context windows, and process larger batch sizes — all of which improve throughput and reduce latency for memory-bound workloads.

Based on TFLOPS per dollar, the A4000 offers better raw compute value at current Shadeform on-demand rates. However, the best choice depends on your specific workload — if you need the extra VRAM or throughput of the A6000, paying the premium may be justified by faster job completion and lower total cost.

The A6000 is currently available across 6 cloud providers on Shadeform's network, compared to 2 for the A4000. Shadeform lets you deploy either GPU across all available providers from a single platform, so you can always find available capacity without manually checking each cloud.

Mixing different GPU types in a single training cluster is generally not recommended, as it creates performance bottlenecks where faster GPUs wait for slower ones. For best results, use a homogeneous cluster of either A6000 or A4000. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore A6000 & A4000 Instances

Browse available instances with A6000 and A4000 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

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