GPU Comparison

Select up to 2 GPUs to analyze their pricing, performance, and specifications side-by-side.

Workstation Verdict

The Quadro RTX 8000 has more VRAM (48GB vs 8GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 50% higher (624 GB/s vs 416 GB/s), translating directly to faster inference throughput. The Quadro RTX 4000 is $3,959 EUR cheaper than the Quadro RTX 8000.

Maximum Capacity Reached. Remove a model to add another. (2/2)

VS
NVIDIA
Quadro RTX 4000
Price
€426
VRAM
8 GB GDDR6
Mem. Speed
416 GB/s
FP32 Compute
7.1 TFLOPS
Key Specs Advantage

Comparable or lower specs

Price
€4,385
VRAM
48 GB GDDR6
Mem. Speed
624 GB/s
FP32 Compute
14.9 TFLOPS
Key Specs Advantage
+110% FP32 (TFLOPS) (14.9 TFLOPS vs 7.1 TFLOPS)
+100% CUDA Cores (4,608 vs 2,304)
+50% Bandwidth (624 GB/s vs 416 GB/s)

Quadro RTX 4000 vs Quadro RTX 8000: In-Depth Breakdown

VRAM: Quadro RTX 4000 vs Quadro RTX 8000

The Quadro RTX 8000 carries 48GB of VRAM versus 8GB on the Quadro RTX 4000. VRAM capacity is the primary constraint for running AI models without quantization — a 70B-parameter model in FP16 requires roughly 140GB, and even smaller models benefit from extra headroom. The 40GB advantage here means the Quadro RTX 8000 can run larger models natively and handle bigger batch sizes in production.

Inference Speed: Memory Bandwidth

Memory bandwidth determines how quickly data is fed to the compute units — it's the main bottleneck for autoregressive inference (token generation in LLMs). The Quadro RTX 8000 delivers 624 GB/s versus 416 GB/s on the Quadro RTX 4000, a 50% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the Quadro RTX 8000 will produce tokens proportionally faster in bandwidth-bound workloads.

AI Training & Compute

For model training, scientific simulation, and rendering, FP32 throughput is the key metric. The Quadro RTX 8000 delivers 14.9 TFLOPS against 7.1 TFLOPS for the Quadro RTX 4000 — a 110% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Quadro RTX 8000.

Price & Value

The Quadro RTX 4000 lists from $426 EUR, $3,959 EUR less than the Quadro RTX 8000 at $4,385 EUR. For budget-constrained teams, the savings may outweigh the spec gap — especially if the smaller card covers your typical workload.

Which should you buy: Quadro RTX 4000 or Quadro RTX 8000?

Choose the Quadro RTX 8000 for maximum capacity — it leads on VRAM, bandwidth, and compute, making it the better fit for large models and training jobs. The Quadro RTX 4000 is the more budget-friendly option ($3,959 EUR less) — a solid choice if your models fit within its 8GB and inference volume is moderate.

Frequently Asked Questions

Can the Quadro RTX 4000 or Quadro RTX 8000 run large language models?

Both can, but the Quadro RTX 8000 (48GB) handles larger models without quantization. The Quadro RTX 4000 (8GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Quadro RTX 4000 or the Quadro RTX 8000?

The Quadro RTX 8000 is faster for token generation — its 624 GB/s memory bandwidth vs 416 GB/s on the Quadro RTX 4000 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The Quadro RTX 8000 has the advantage at 14.9 TFLOPS vs 7.1 TFLOPS, making training runs proportionally faster than on the Quadro RTX 4000.

Technical Specifications Comparison

Architecture & Cores

SpecificationQuadro RTX 4000Quadro RTX 8000
ArchitectureTuringTuring
CUDA Cores (CUDA Cores / CUDA Cores)2,3044,608

Memory

SpecificationQuadro RTX 4000Quadro RTX 8000
VRAM Capacity8 GB48 GB
Memory TypeGDDR6GDDR6
Memory Bus256-bit384-bit
Bandwidth416 GB/s624 GB/s

Connectivity & Power

SpecificationQuadro RTX 4000Quadro RTX 8000
InterfacePCIe 3.0 x16PCIe 3.0 x16
TDP160 W295 W
ReleasedOct 2018Oct 2018

Workstation

SpecificationQuadro RTX 4000Quadro RTX 8000
FP32 (TFLOPS)7.1 TFLOPS14.9 TFLOPS
ECCYesYes
NVLinkNoYes
Form factorsingle-slotdual-slot