GPU Comparison

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

Workstation Verdict

The RTX A4500 has more VRAM (20GB vs 16GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 43% higher (640 GB/s vs 448 GB/s), translating directly to faster inference throughput. The RTX A4500 is $57 EUR cheaper than the RTX A4000.

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

VS
NVIDIA
RTX A4000
Price
€1,259
VRAM
16 GB GDDR6
Mem. Speed
448 GB/s
FP32 Compute
19.2 TFLOPS
Key Specs Advantage

Comparable or lower specs

NVIDIA
RTX A4500
Price
€1,202
VRAM
20 GB GDDR6
Mem. Speed
640 GB/s
FP32 Compute
23.7 TFLOPS
Key Specs Advantage
+43% Bandwidth (640 GB/s vs 448 GB/s)
+25% Memory Bus (320-bit vs 256-bit)
+23% FP32 (TFLOPS) (23.7 TFLOPS vs 19.2 TFLOPS)

RTX A4000 vs RTX A4500: In-Depth Breakdown

VRAM: RTX A4000 vs RTX A4500

The RTX A4500 carries 20GB of VRAM versus 16GB on the RTX A4000. 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 4GB advantage here means the RTX A4500 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 RTX A4500 delivers 640 GB/s versus 448 GB/s on the RTX A4000, a 43% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the RTX A4500 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 RTX A4500 delivers 23.7 TFLOPS against 19.2 TFLOPS for the RTX A4000 — a 23% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX A4500.

Price & Value

The RTX A4500 lists from $1,202 EUR, $57 EUR less than the RTX A4000 at $1,259 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: RTX A4000 or RTX A4500?

The RTX A4500 is the stronger choice for large-model workloads where VRAM is the bottleneck. The RTX A4000 is more economical at $57 EUR less, and sufficient if your models fit within its 16GB.

Frequently Asked Questions

Can the RTX A4000 or RTX A4500 run large language models?

Both can, but the RTX A4500 (20GB) handles larger models without quantization. The RTX A4000 (16GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the RTX A4000 or the RTX A4500?

The RTX A4500 is faster for token generation — its 640 GB/s memory bandwidth vs 448 GB/s on the RTX A4000 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The RTX A4500 has the advantage at 23.7 TFLOPS vs 19.2 TFLOPS, making training runs proportionally faster than on the RTX A4000.

Technical Specifications Comparison

Architecture & Cores

SpecificationRTX A4000RTX A4500
ArchitectureAmpereAmpere
CUDA Cores (CUDA Cores / CUDA Cores)6,1447,168

Memory

SpecificationRTX A4000RTX A4500
VRAM Capacity16 GB20 GB
Memory TypeGDDR6GDDR6
Memory Bus256-bit320-bit
Bandwidth448 GB/s640 GB/s

Connectivity & Power

SpecificationRTX A4000RTX A4500
InterfacePCIe 4.0 x16PCIe 4.0 x16
TDP140 W200 W
ReleasedApr 2021Oct 2021

Workstation

SpecificationRTX A4000RTX A4500
FP32 (TFLOPS)19.2 TFLOPS23.7 TFLOPS
ECCYesYes
NVLinkNoYes
Form factorsingle-slotdual-slot