A5000 vs L40S
Explore a head to head comparison of specifications, performance, and pricing.
A5000
The NVIDIA A5000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
L40S
The NVIDIA L40S delivers high-performance computing capabilities for AI, machine learning, and data science applications.
A5000 vs L40S: Which Should You Choose?
The L40S offers 48 GB of VRAM — 2× the 24 GB on the A5000 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the L40S delivers 91.61 TFLOPS versus 27.77 TFLOPS on the A5000 — 3× faster for mixed-precision training and inference. Memory bandwidth favors the L40S at 0.86 TB/s compared to 0.77 TB/s on the A5000, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the A5000 is built on Ampere while the L40S uses Ada Lovelace, reflecting different generational capabilities and optimizations. On Shadeform, the A5000 starts from $0.44/hr versus $0.74/hr for the L40S — 68% more expensive — reflecting the performance premium. The L40S is available across 7 cloud providers on Shadeform compared to 2 for the A5000, giving more options for region and pricing flexibility.
A5000 — 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 A5000 when:
- ✓24 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
L40S — Best Use Cases
- •LLM inference and model serving
- •Image generation and diffusion models
- •Smaller fine-tuning runs
- •Cost-efficient GPU compute
Choose L40S 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
See how the A5000 & L40S compare
Compare detailed hardware specifications and average pricing for the A5000 and L40S.
Compare Hardware Specifications
| A5000 | L40S | |
|---|---|---|
| GPU Type | A5000 | L40S |
| VRAM per GPU | 24 GB | 48 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Ampere | Ada Lovelace |
| Interconnect | PCIe Gen4 | PCIe Gen4 |
| Memory Bandwidth | 768 GB/s | 864 GB/s |
| FP16 TFLOPS | 27.77 TFLOPS (1:1) | 91.61 TFLOPS (1:1) |
| CUDA Cores | 8192 | 18176 |
| Tensor Cores | 256 (3rd Gen) | 568 (4th Gen) |
| RT Cores | 64 (2nd Gen) | 142 (3rd Gen) |
| Base Clock | 1170 MHz | 1110 MHz |
| Boost Clock | 1695 MHz | 2520 MHz |
| TDP | 230W | 350W |
| Process Node | TSMC 8nm | TSMC 4N |
| Data Formats | INT8, BF16, FP16, TF32, FP32 | INT4, INT8, FP8, BF16, FP16, TF32, FP32 |
Compare Average On-Demand Pricing
| A5000 | L40S | |
|---|---|---|
| 1 GPU | $0.93 /hr | $1.28 /hr |
| 2 GPUs | $1.86 /hr | $2.69 /hr |
| 4 GPUs | $3.72 /hr | $5.37 /hr |
| 8 GPUs | $3.52 /hr | $8.95 /hr |
Frequently Asked Questions: A5000 vs L40S
The main differences are VRAM (24 GB vs 48 GB), FP16 throughput (27.77 vs 91.61 TFLOPS), architecture (Ampere vs Ada Lovelace). The A5000 uses the Ampere architecture while the L40S is based on Ada Lovelace, giving each GPU different generational capabilities.
The L40S 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 A5000 is available from $0.44/hr. The L40S starts from $0.74/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.
The L40S has more VRAM at 48 GB, compared to 24 GB on the A5000. 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 L40S 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 A5000, paying the premium may be justified by faster job completion and lower total cost.
The L40S is currently available across 7 cloud providers on Shadeform's network, compared to 2 for the A5000. 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 A5000 or L40S. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
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