AMD Radeon RX 7900 XTX vs NVIDIA L40S

Side-by-side comparison of AMD Radeon RX 7900 XTX (24 GB VRAM, 960 GB/s) and NVIDIA L40S (48 GB VRAM, 864 GB/s). Compare specs, compute throughput, and workload sizing for LLM inference.

Decision Summary

Spec	AMD Radeon RX 7900 XTX	NVIDIA L40S
VRAM	24GB GDDR6	48GB GDDR6
Memory Bandwidth	960 GB/s	864 GB/s
FP8 TFLOPS	—	733
FP16 TFLOPS	61.4	366
Interconnect	PCIe 4.0 (64 GB/s)	PCIe 4.0 (64 GB/s)
TDP	355W	350W
Recommended Quantization	GGUF / AWQ — INT4 mandatory for 13B+	AWQ / GPTQ / GGUF — INT4 essential for 30B+ models

Compare for a Workload

Configure a workload to see how each selected GPU performs. Calculations are deterministic estimates based on architectural specifications.

Workload

Context Length

Precision

Batch Size

Configure workload parameters above and click "Calculate VRAM Requirement" to see results.

Cloud Provider Pricing

Current spot and on-demand rates across providers for AMD Radeon RX 7900 XTX and NVIDIA L40S.

Featured GPU Pricing Pages

NVIDIA H100 SXM5

80GB HBM3 • 3.35 TB/s • NVLink 4.0

NVIDIA A100 40GB

40GB HBM2 • 1.55 TB/s • NVLink 3.0

NVIDIA A100 80GB

Verified spot rates & reserved pricing

NVIDIA A10G

24GB GDDR6 • 0.62 TB/s • PCIe 4.0

NVIDIA RTX 3090

24GB GDDR6X • 0.94 TB/s • PCIe 4.0

NVIDIA T4

16GB GDDR6 • 0.32 TB/s • PCIe 3.0

	Provider	GPU & VRAM	Interconnect	Spot Price ($/hr)	On-Demand ($/hr)	Monthly ($/720h)	Status	Action
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On-demand and monthly figures are the providers' listed rates (monthly = listed rate, else hourly × 720h). Rows without a tracked rate show —. All rates subject to preemption and provider availability.

Data Freshness: Public Cloud APIs & Market Scraping | Refreshed Daily (UTC)|Benchmark Baseline: Ubuntu 24.04, CUDA 12.4, vLLM v0.6.x, PagedAttention v2, FlashAttention-3

Prices verified daily from Spheron, RunPod, Vast.ai, and Lambda Labs APIs.

Microarchitecture & Interconnect

AMD Radeon RX 7900 XTX

ArchitectureRDNA 3

Process Node5nm TSMC

FP8 TFLOPS—

FP16 TFLOPS61.4

Compute BoundMemory-bandwidth bound at large batch; compute-bound at small batch with FP8/BF16

Recommended TopologyPCIe Single Node — consumer GPU

Recommended Quantization: GGUF / AWQ — INT4 mandatory for 13B+

NVIDIA L40S

ArchitectureAda Lovelace AD102

Process Node5nm TSMC

FP8 TFLOPS733

FP16 TFLOPS366

Compute BoundSeverely memory-bandwidth bound — GDDR6 bus cannot feed FP8 Tensor Core demand at batch≥16

Recommended TopologyPCIe Single Node — no NVLink, 2-4 GPU max

Recommended Quantization: AWQ / GPTQ / GGUF — INT4 essential for 30B+ models

Related GPU Comparisons

Explore canonical side-by-side comparisons for this hardware tier.

AMD Radeon RX 7900 XTX vs NVIDIA GeForce RTX 4090→

24GB GDDR6 vs 24GB GDDR6X

NVIDIA H100 SXM5 vs NVIDIA L40S→

80GB HBM3 vs 48GB GDDR6

NVIDIA A100 80GB SXM4 vs NVIDIA L40S→

80GB HBM2e vs 48GB GDDR6

NVIDIA L40S vs NVIDIA GeForce RTX 4090→

48GB GDDR6 vs 24GB GDDR6X

Deploy AMD Radeon RX 7900 XTX Deploy NVIDIA L40S

Data Freshness: Verified via Public Cloud APIs & Market Scraping | Refreshed Daily (UTC)|Benchmark Baseline: Ubuntu 24.04, CUDA 12.4, vLLM v0.6.x (PagedAttention v2, FlashAttention-3), BF16/FP8 weights.

Methodology →