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Quadro RTX 4000 vs Quadro RTX 6000

Workstation Verdict

With 24GB on board versus 8GB for the Quadro RTX 4000, the Quadro RTX 6000 carries more headroom for large models and memory-hungry workloads. Its memory bandwidth is 50% higher (624 GB/s vs 416 GB/s), translating directly to faster inference throughput.

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

VS
Price
S$1,447βœ“
VRAM
8 GB GDDR6
Mem. Speed
416 GB/s
FP32 Compute
7.1 TFLOPS
Key Specs Advantage

Comparable or lower specs

Price
Reference GPU
VRAM
24 GB GDDR6βœ“
Mem. Speed
624 GB/sβœ“
FP32 Compute
16.3 TFLOPSβœ“
Key Specs Advantage
+130% FP32 (TFLOPS) (16.3 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 6000: In-Depth Breakdown

VRAM: Quadro RTX 4000 vs Quadro RTX 6000

With 24GB of VRAM against the Quadro RTX 4000's 8GB, the Quadro RTX 6000 has a 16GB edge. VRAM is what determines whether a model fits without quantization at all β€” a 70B-parameter model in FP16 needs around 140GB, and smaller models still benefit from spare capacity. That extra headroom lets the Quadro RTX 6000 load bigger models and run larger production batch sizes.

Inference Speed: Memory Bandwidth

Memory bandwidth determines how quickly data is fed to the compute units β€” it's the main bottleneck for autoregressive inference (token generation in LLMs). The Quadro RTX 6000 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 6000 will produce tokens proportionally faster in bandwidth-bound workloads.

AI Training & Compute

FP32 throughput is the metric that matters most for training, scientific simulation, and rendering work. The Quadro RTX 6000 posts 16.3 TFLOPS versus 7.1 TFLOPS on the Quadro RTX 4000, a 130% compute lead. Expect training jobs and heavy matrix math to finish proportionally sooner on the Quadro RTX 6000.

Which should you buy: Quadro RTX 4000 or Quadro RTX 6000?

For large-model workloads bottlenecked on VRAM, the Quadro RTX 6000 is the better pick. The Quadro RTX 4000 costs less and holds up fine if your models fit inside its 8GB.

Frequently Asked Questions

Can the Quadro RTX 4000 or Quadro RTX 6000 run large language models?

Both can, but the Quadro RTX 6000 (24GB) 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 6000?

The Quadro RTX 6000 generates tokens faster: its 624 GB/s of memory bandwidth against 416 GB/s on the Quadro RTX 4000 is the main factor behind inference throughput in autoregressive models.

Which is better for AI training?

The Quadro RTX 6000 has the advantage at 16.3 TFLOPS vs 7.1 TFLOPS, making training runs proportionally faster than on the Quadro RTX 4000.

Which should you buy: Quadro RTX 4000 or Quadro RTX 6000?

For large-model workloads bottlenecked on VRAM, the Quadro RTX 6000 is the better pick. The Quadro RTX 4000 costs less and holds up fine if your models fit inside its 8GB.

Technical Specifications Comparison

Architecture & Cores

Architecture & Cores specifications comparison between Quadro RTX 4000 and Quadro RTX 6000
SpecificationQuadro RTX 4000Quadro RTX 6000
ArchitectureTuringTuring
CUDA Cores (CUDA Cores / CUDA Cores)2,3044,608βœ“

Memory

Memory specifications comparison between Quadro RTX 4000 and Quadro RTX 6000
SpecificationQuadro RTX 4000Quadro RTX 6000
VRAM Capacity8 GB24 GBβœ“
Memory TypeGDDR6GDDR6
Memory Bus256-bit384-bitβœ“
Bandwidth416 GB/s624 GB/sβœ“

Connectivity & Power

Connectivity & Power specifications comparison between Quadro RTX 4000 and Quadro RTX 6000
SpecificationQuadro RTX 4000Quadro RTX 6000
InterfacePCIe 3.0 x16PCIe 3.0 x16
TDP160 Wβœ“295 W
ReleasedOct 2018Oct 2018

Workstation

Workstation specifications comparison between Quadro RTX 4000 and Quadro RTX 6000
SpecificationQuadro RTX 4000Quadro RTX 6000
FP32 (TFLOPS)7.1 TFLOPS16.3 TFLOPSβœ“
ECCYesYes
NVLinkNoYesβœ“
Form factorsingle-slotdual-slot