L40S vs AMD Radeon RX 7900 XTX

Detailed comparison of specifications, performance, and pricing between L40S and AMD Radeon RX 7900 XTX

Comparing:
🏆
Overall Winner
L40S
Wins 3 of 7 categories
Performance Leader
L40S
733.0 TFLOPS (+501%)
The L40S is 501% faster.

Difference Analysis

Metric
L40S
Difference
AMD Radeon RX 7900 XTX
Tensor TFLOPS
733.0
+501%
122.0
VRAM
48GB
+100%
24GB
Memory Bandwidth
864 GB/s
-11%
960 GB/s
Hardware Price
$$9.0k
=
-
Cloud Price/hr
$1.09
=
-

Full Specifications

Specification L40S AMD Radeon RX 7900 XTX B200
Brand NVIDIA AMD NVIDIA
Series Data Center Consumer Data Center
Architecture Ada Lovelace RDNA 3 Blackwell
VRAM 48GB 24GB 192GB
VRAM Type GDDR6 GDDR6 HBM3e
Memory Bandwidth 864 GB/s 960 GB/s 8.0 TB/s
FP16 TFLOPS 183.0 122.0 -
Tensor TFLOPS 733.0 - 4.5k
TDP 350W 355W 1000W
Form Factor PCIe - SXM
Hardware Price $$9.0k - $$45k
Cloud Price (min) $1.09/hr - $3.75/hr

Which Should You Choose?

🧠

For AI Training

Large model training needs maximum VRAM and memory bandwidth.

Recommended: L40S
48GB VRAM · 864 GB/s

For AI Inference

Inference prioritizes throughput and cost efficiency.

Recommended: L40S
Best performance per dollar

L40S vs AMD Radeon RX 7900 XTX FAQ

It depends on your use case. The L40S offers 501% better performance (733.0 vs 122.0 TFLOPS). For raw performance, choose L40S. For value, consider your budget and workload requirements.

The L40S has more VRAM with 48GB compared to 24GB (100% more). More VRAM is crucial for training large models and running inference on bigger batch sizes.

For AI training, the L40S is generally better due to its larger VRAM (48GB). Large language models and deep learning workloads benefit significantly from more memory. However, if your models fit in 24GB, the cheaper option may be more cost-effective.

Price comparison requires both GPUs to have available pricing data. Check individual GPU pages for current market prices.

Upgrading to L40S would give you 501% more performance and 100% more VRAM. Consider if your workloads are bottlenecked by current GPU capabilities.

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