GPU Comparison

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

Workstation Verdict

The RTX 5000 Ada Generation has more VRAM (32GB vs 12GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 100% higher (576 GB/s vs 288 GB/s), translating directly to faster inference throughput. The RTX A2000 is $4,150 USD cheaper than the RTX 5000 Ada Generation.

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

VS
Price
$4,500 USD
VRAM
32 GB GDDR6
Mem. Speed
576 GB/s
FP32 Compute
65.3 TFLOPS
Key Specs Advantage
+716% FP32 (TFLOPS) (65.3 TFLOPS vs 8 TFLOPS)
+285% CUDA Cores (12,800 vs 3,328)
+100% Bandwidth (576 GB/s vs 288 GB/s)
NVIDIA
RTX A2000
Price
$350 USD
VRAM
12 GB GDDR6
Mem. Speed
288 GB/s
FP32 Compute
8 TFLOPS
Key Specs Advantage

Comparable or lower specs

RTX 5000 Ada Generation vs RTX A2000: In-Depth Breakdown

VRAM: RTX 5000 Ada Generation vs RTX A2000

The RTX 5000 Ada Generation carries 32GB of VRAM versus 12GB on the RTX A2000. 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 20GB advantage here means the RTX 5000 Ada Generation 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 5000 Ada Generation delivers 576 GB/s versus 288 GB/s on the RTX A2000, a 100% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the RTX 5000 Ada Generation 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 5000 Ada Generation delivers 65.3 TFLOPS against 8 TFLOPS for the RTX A2000 — a 716% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX 5000 Ada Generation.

Price & Value

The RTX A2000 lists from $350 USD, $4,150 USD less than the RTX 5000 Ada Generation at $4,500 USD. 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 5000 Ada Generation or RTX A2000?

Choose the RTX 5000 Ada Generation for maximum capacity — it leads on VRAM, bandwidth, and compute, making it the better fit for large models and training jobs. The RTX A2000 is the more budget-friendly option ($4,150 USD less) — a solid choice if your models fit within its 12GB and inference volume is moderate.

Frequently Asked Questions

Can the RTX 5000 Ada Generation or RTX A2000 run large language models?

Both can, but the RTX 5000 Ada Generation (32GB) handles larger models without quantization. The RTX A2000 (12GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the RTX 5000 Ada Generation or the RTX A2000?

The RTX 5000 Ada Generation is faster for token generation — its 576 GB/s memory bandwidth vs 288 GB/s on the RTX A2000 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The RTX 5000 Ada Generation has the advantage at 65.3 TFLOPS vs 8 TFLOPS, making training runs proportionally faster than on the RTX A2000.

Technical Specifications Comparison

Architecture & Cores

SpecificationRTX 5000 Ada GenerationRTX A2000
ArchitectureAda LovelaceAmpere
CUDA Cores (CUDA Cores / CUDA Cores)12,8003,328

Memory

SpecificationRTX 5000 Ada GenerationRTX A2000
VRAM Capacity32 GB12 GB
Memory TypeGDDR6GDDR6
Memory Bus256-bit192-bit
Bandwidth576 GB/s288 GB/s

Connectivity & Power

SpecificationRTX 5000 Ada GenerationRTX A2000
InterfacePCIe 4.0 x16PCIe 4.0 x16
TDP250 W70 W
ReleasedNov 2022Aug 2021

Workstation

SpecificationRTX 5000 Ada GenerationRTX A2000
FP32 (TFLOPS)65.3 TFLOPS8 TFLOPS
ECCYesYes
NVLinkNoNo
Form factordual-slotlow-profile