Shadeform primary logo

A4000 vs L4

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

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

L4

The NVIDIA L4 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$3.56/hr
GPU VRAM24 GB
Cloud Availability1 clouds
System Memory384 GB
CPU Cores64
Storage500 GB

A4000 vs L4: Which Should You Choose?

The L4 offers 24 GB of VRAM — 1.5× 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 L4 delivers 30.29 TFLOPS versus 19.17 TFLOPS on the A4000 — 1.6× faster for mixed-precision training and inference. Memory bandwidth favors the A4000 at 0.45 TB/s compared to 0.30 TB/s on the L4, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the A4000 is built on Ampere while the L4 uses Ada Lovelace, reflecting different generational capabilities and optimizations. On Shadeform, the A4000 starts from $0.15/hr versus $0.95/hr for the L4 — 533% more expensive — reflecting the performance premium. The A4000 is available across 2 cloud providers on Shadeform compared to 1 for the L4, giving more options for region and pricing flexibility.

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
  • You need flexibility across multiple cloud providers or regions

L4 — Best Use Cases

  • LLM inference and model serving
  • Image generation and diffusion models
  • Smaller fine-tuning runs
  • Cost-efficient GPU compute

Choose L4 when:

  • You need 24 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
  • Your preferred provider already has availability

See how the A4000 & L4 compare

Compare detailed hardware specifications and average pricing for the A4000 and L4.

Compare Hardware Specifications

A4000L4
GPU Type
A4000
L4
VRAM per GPU
16 GB
24 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Ampere
Ada Lovelace
Interconnect
PCIe Gen4
PCIe Gen4
Memory Bandwidth
448 GB/s
300 GB/s
FP16 TFLOPS
19.17 TFLOPS (1:1)
30.29 TFLOPS (1:1)
CUDA Cores
6144
7424
Tensor Cores
192 (3rd Gen)
232 (4th Gen)
RT Cores
48 (2nd Gen)
58 (3rd Gen)
Base Clock
735 MHz
795 MHz
Boost Clock
1695 MHz
2040 MHz
TDP
140W
72W
Process Node
TSMC 8nm
TSMC 4N
Data Formats
INT8, BF16, FP16, TF32, FP32
FP8, INT8, BF16, FP16, TF32, FP32

Compare Average On-Demand Pricing

A4000L4
1 GPU
$0.47 /hr
$0.95 /hr
2 GPUs
$0.95 /hr
$1.90 /hr
4 GPUs
$1.90 /hr
$3.80 /hr
8 GPUs
$1.20 /hr
$7.60 /hr

Frequently Asked Questions: A4000 vs L4

The main differences are VRAM (16 GB vs 24 GB), FP16 throughput (19.17 vs 30.29 TFLOPS), architecture (Ampere vs Ada Lovelace). The A4000 uses the Ampere architecture while the L4 is based on Ada Lovelace, giving each GPU different generational capabilities.

The L4 is generally better for large language model training due to its higher throughput and 24 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 L4 starts from $0.95/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.

The L4 has more VRAM at 24 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 L4, paying the premium may be justified by faster job completion and lower total cost.

The A4000 is currently available across 2 cloud providers on Shadeform's network, compared to 1 for the L4. 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 A4000 or L4. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore A4000 & L4 Instances

Browse available instances with A4000 and L4 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

Explore more GPU comparisons

Select any two GPUs to compare their specifications and explore pricing across providers.

Manage 30+ GPU clouds in one platform