NVIDIA GeForce RTX 4090 vs NVIDIA RTX 6000 Ada Generation

Side-by-side comparison of NVIDIA GeForce RTX 4090 (24 GB VRAM, 1.0 TB/s) and NVIDIA RTX 6000 Ada Generation (48 GB VRAM, 960 GB/s). Compare specs, compute throughput, and workload sizing for LLM inference.

Decision Summary

Spec	NVIDIA GeForce RTX 4090	NVIDIA RTX 6000 Ada Generation
VRAM	24GB GDDR6X	48GB GDDR6
Memory Bandwidth	1.0 TB/s	960 GB/s
FP8 TFLOPS	165	733
FP16 TFLOPS	82.6	366
Interconnect	PCIe 4.0 (64 GB/s)	PCIe 4.0 (64 GB/s)
TDP	450W	300W
Recommended Quantization	GGUF / AWQ / GPTQ — INT4 mandatory for 13B+	AWQ / GPTQ — INT4 for 30B+, FP8 for 7B-13B

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 GeForce RTX 4090 and NVIDIA RTX 6000 Ada Generation.

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	RTX 409024GB GDDR6X Llama 8B ✅Qwen 32B (INT4) ✅FLUX.1 (FP8) ✅70B Models ⚠️ (INT3/Offload)	PCIe 4.0 (64 GB/s)	$0.34/hr Calculated EstimateMEDIUM SourceVast.ai VerifiedSep 26, 2026 Value 0.34 /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	$0.34 / hr	$208 / mo	Instant	Deploy →
RunPod Cloud	RTX 409024GB GDDR6X Llama 8B ✅Qwen 32B (INT4) ✅FLUX.1 (FP8) ✅70B Models ⚠️ (INT3/Offload)	PCIe 4.0 (64 GB/s)	$0.39/hr Observed Spot RateMEDIUM SourceRunPod VerifiedSep 26, 2026 Value 0.39 /hr Methodology Explicit spot listing from the provider. On-demand is the provider's listed hourly rate. Assumptions & Parameters note: Spot rates fluctuate with capacity Refreshed daily from provider APIs and market scrapingSep 26, 2026	$0.74 / hr	$453 / mo	Instant	Deploy →
Spheron Bare Metal	RTX 409024GB GDDR6X Llama 8B ✅Qwen 32B (INT4) ✅FLUX.1 (FP8) ✅70B Models ⚠️ (INT3/Offload)	PCIe 4.0 (64 GB/s)	$0.69/hr Calculated EstimateMEDIUM SourceSpheron 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 →
Lambda Labs Dedicated	RTX 409024GB GDDR6X Llama 8B ✅Qwen 32B (INT4) ✅FLUX.1 (FP8) ✅70B Models ⚠️ (INT3/Offload)	PCIe 4.0 (64 GB/s)	$0.89/hr Calculated EstimateMEDIUM SourceLambda Labs VerifiedSep 26, 2026 Value 0.89 /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	$0.89 / hr	$545 / 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 GeForce RTX 4090

ArchitectureAda Lovelace AD102

Process Node5nm TSMC

FP8 TFLOPS165

FP16 TFLOPS82.6

Compute BoundExtremely memory-bandwidth bound — GDDR6X 1 TB/s cannot sustain FP16 inference at batch≥4

Recommended TopologyPCIe Single Node — 2 GPU max for training

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

NVIDIA RTX 6000 Ada Generation

ArchitectureAda Lovelace AD102

Process Node5nm TSMC

FP8 TFLOPS733

FP16 TFLOPS366

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

Recommended TopologyPCIe Single Node — ECC memory for enterprise workloads

Recommended Quantization: AWQ / GPTQ — INT4 for 30B+, FP8 for 7B-13B

Related GPU Comparisons

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

NVIDIA A100 80GB SXM4 vs NVIDIA GeForce RTX 4090→

80GB HBM2e vs 24GB GDDR6X

NVIDIA L40S vs NVIDIA GeForce RTX 4090→

48GB GDDR6 vs 24GB GDDR6X

NVIDIA H100 SXM5 vs NVIDIA GeForce RTX 4090→

80GB HBM3 vs 24GB GDDR6X

NVIDIA L40S vs NVIDIA RTX 6000 Ada Generation→

48GB GDDR6 vs 48GB GDDR6

Deploy NVIDIA GeForce RTX 4090 Deploy NVIDIA RTX 6000 Ada Generation

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 →