L40S vs RTX 6000 Ada
Explore a head to head comparison of specifications, performance, and pricing.
L40S
The NVIDIA L40S delivers high-performance computing capabilities for AI, machine learning, and data science applications.
RTX 6000 Ada
The NVIDIA RTX 6000 Ada delivers high-performance computing capabilities for AI, machine learning, and data science applications.
L40S vs RTX 6000 Ada: Which Should You Choose?
Both the L40S and RTX 6000 Ada offer 48 GB of VRAM, putting them on equal footing for memory-bound workloads. On FP16 throughput, the L40S delivers 91.61 TFLOPS versus 91.06 TFLOPS on the RTX 6000 Ada — 1% more faster for mixed-precision training and inference. Memory bandwidth favors the RTX 6000 Ada at 0.96 TB/s compared to 0.86 TB/s on the L40S, which directly impacts inference latency for memory-bandwidth-bound models. On Shadeform, the L40S starts from $0.74/hr versus $0.97/hr for the RTX 6000 Ada — 31% more expensive — reflecting the performance premium. The L40S is available across 7 cloud providers on Shadeform compared to 4 for the RTX 6000 Ada, giving more options for region and pricing flexibility.
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:
- ✓Cost efficiency is your primary concern
- ✓You are training large models or running high-throughput inference
- ✓You need flexibility across multiple cloud providers or regions
RTX 6000 Ada — Best Use Cases
- •LLM inference and model serving
- •Image generation and diffusion models
- •Smaller fine-tuning runs
- •Cost-efficient GPU compute
Choose RTX 6000 Ada when:
- ✓Maximum performance justifies the higher cost
- ✓Your workload does not require peak FP16 throughput
- ✓Your preferred provider already has availability
See how the L40S & RTX 6000 Ada compare
Compare detailed hardware specifications and average pricing for the L40S and RTX 6000 Ada.
Compare Hardware Specifications
| L40S | RTX 6000 Ada | |
|---|---|---|
| GPU Type | L40S | RTX 6000 Ada |
| VRAM per GPU | 48 GB | 48 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Ada Lovelace | Ada Lovelace |
| Interconnect | PCIe Gen4 | PCIe Gen4 |
| Memory Bandwidth | 864 GB/s | 960 GB/s |
| FP16 TFLOPS | 91.61 TFLOPS (1:1) | 91.06 TFLOPS (1:1) |
| CUDA Cores | 18176 | 18176 |
| Tensor Cores | 568 (4th Gen) | 568 (4th Gen) |
| RT Cores | 142 (3rd Gen) | 142 (3rd Gen) |
| Base Clock | 1110 MHz | 915 MHz |
| Boost Clock | 2520 MHz | 2505 MHz |
| TDP | 350W | 300W |
| Process Node | TSMC 4N | TSMC 4N |
| Data Formats | INT4, INT8, FP8, BF16, FP16, TF32, FP32 | FP8, INT8, BF16, FP16, TF32, FP32 |
Compare Average On-Demand Pricing
| L40S | RTX 6000 Ada | |
|---|---|---|
| 1 GPU | $1.27 /hr | $1.20 /hr |
| 2 GPUs | $2.60 /hr | $2.04 /hr |
| 4 GPUs | $5.18 /hr | $3.88 /hr |
| 8 GPUs | $8.70 /hr | $7.01 /hr |
Frequently Asked Questions: L40S vs RTX 6000 Ada
The main differences are FP16 throughput (91.61 vs 91.06 TFLOPS).
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 L40S is available from $0.74/hr. The RTX 6000 Ada starts from $0.97/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.
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 RTX 6000 Ada, 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 4 for the RTX 6000 Ada. 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 L40S or RTX 6000 Ada. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
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