NVIDIA L40S vs NVIDIA RTX 3060 12GB

Side-by-side comparison of NVIDIA L40S (48 GB VRAM, 864 GB/s) and NVIDIA RTX 3060 12GB (12 GB VRAM, 360 GB/s). Compare specs, compute throughput, and workload sizing for LLM inference.

Decision Summary

Spec	NVIDIA L40S	NVIDIA RTX 3060 12GB
VRAM	48GB GDDR6	12GB GDDR6
Memory Bandwidth	864 GB/s	360 GB/s
FP8 TFLOPS	733	—
FP16 TFLOPS	366	26.4
Interconnect	PCIe 4.0 (64 GB/s)	PCIe 4.0 (64 GB/s)
TDP	350W	170W
Recommended Quantization	AWQ / GPTQ / GGUF — INT4 essential for 30B+ models	GGUF / AWQ — INT4 mandatory

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 NVIDIA L40S and NVIDIA RTX 3060 12GB.

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
Vast.ai Community	L40S48GB GDDR6 Llama 8B ✅Qwen 24B ✅FLUX.1 (FP8) ✅70B Models ❌	PCIe 4.0 (64 GB/s)	$0.69/hr Calculated EstimateMEDIUM SourceVast.ai VerifiedSep 26, 2026 Value 0.69 /hr Methodology No distinct spot listing — the provider's listed hourly (on-demand) rate is surfaced as the tracked rate. Assumptions & Parameters note: Spot rates fluctuate with capacity Refreshed daily from provider APIs and market scrapingSep 26, 2026	$0.69 / hr	$422 / mo	Instant	Deploy →
RunPod Cloud	L40S48GB GDDR6 Llama 8B ✅Qwen 24B ✅FLUX.1 (FP8) ✅70B Models ❌	PCIe 4.0 (64 GB/s)	$1.09/hr Calculated EstimateMEDIUM SourceRunPod VerifiedSep 26, 2026 Value 1.09 /hr Methodology No distinct spot listing — the provider's listed hourly (on-demand) rate is surfaced as the tracked rate. Assumptions & Parameters note: Spot rates fluctuate with capacity Refreshed daily from provider APIs and market scrapingSep 26, 2026	$1.09 / hr	$667 / mo	Instant	Deploy →
Spheron Bare Metal	L40S48GB GDDR6 Llama 8B ✅Qwen 24B ✅FLUX.1 (FP8) ✅70B Models ❌	PCIe 4.0 (64 GB/s)	$1.19/hr Calculated EstimateMEDIUM SourceSpheron VerifiedSep 26, 2026 Value 1.19 /hr Methodology No distinct spot listing — the provider's listed hourly (on-demand) rate is surfaced as the tracked rate. Assumptions & Parameters note: Spot rates fluctuate with capacity Refreshed daily from provider APIs and market scrapingSep 26, 2026	$1.19 / hr	$728 / mo	Instant	Deploy →
Lambda Labs Dedicated	L40S48GB GDDR6 Llama 8B ✅Qwen 24B ✅FLUX.1 (FP8) ✅70B Models ❌	PCIe 4.0 (64 GB/s)	$1.49/hr Calculated EstimateMEDIUM SourceLambda Labs VerifiedSep 26, 2026 Value 1.49 /hr Methodology No distinct spot listing — the provider's listed hourly (on-demand) rate is surfaced as the tracked rate. Assumptions & Parameters note: Spot rates fluctuate with capacity Refreshed daily from provider APIs and market scrapingSep 26, 2026	$1.49 / hr	$912 / mo	Instant	Deploy →

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

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

NVIDIA RTX 3060 12GB

ArchitectureAmpere GA102

Process Node8nm Samsung

FP8 TFLOPS—

FP16 TFLOPS26.4

Compute BoundMemory-bound — GDDR6 bus cannot feed compute units even at modest batch sizes

Recommended TopologyPCIe Single Node — budget edge

Recommended Quantization: GGUF / AWQ — INT4 mandatory

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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

NVIDIA RTX 3060 12GB vs NVIDIA GeForce RTX 4090→

12GB GDDR6 vs 24GB GDDR6X

Deploy NVIDIA L40S Deploy NVIDIA RTX 3060 12GB

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 →