GPU Comparison

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

Workstation Verdict

The RTX A6000 has more VRAM (48GB vs 16GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 243% higher (768 GB/s vs 224 GB/s), translating directly to faster inference throughput. The RTX 2000 Ada Generation is $6,506 GBP cheaper than the RTX A6000.

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

VS
NVIDIA
RTX 2000 Ada Generation
Price
£650
VRAM
16 GB GDDR6
Mem. Speed
224 GB/s
FP32 Compute
12 TFLOPS
Key Specs Advantage

Comparable or lower specs

NVIDIA
RTX A6000
Price
£7,156
VRAM
48 GB GDDR6
Mem. Speed
768 GB/s
FP32 Compute
38.7 TFLOPS
Key Specs Advantage
+282% CUDA Cores (10,752 vs 2,816)
+243% Bandwidth (768 GB/s vs 224 GB/s)
+223% FP32 (TFLOPS) (38.7 TFLOPS vs 12 TFLOPS)

RTX 2000 Ada Generation vs RTX A6000: In-Depth Breakdown

VRAM: RTX 2000 Ada Generation vs RTX A6000

The RTX A6000 carries 48GB of VRAM versus 16GB on the RTX 2000 Ada Generation. 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 32GB advantage here means the RTX A6000 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 A6000 delivers 768 GB/s versus 224 GB/s on the RTX 2000 Ada Generation, a 243% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the RTX A6000 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 A6000 delivers 38.7 TFLOPS against 12 TFLOPS for the RTX 2000 Ada Generation — a 223% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX A6000.

Price & Value

The RTX 2000 Ada Generation lists from $650 GBP, $6,506 GBP less than the RTX A6000 at $7,156 GBP. 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 2000 Ada Generation or RTX A6000?

Choose the RTX A6000 for maximum capacity — it leads on VRAM, bandwidth, and compute, making it the better fit for large models and training jobs. The RTX 2000 Ada Generation is the more budget-friendly option ($6,506 GBP less) — a solid choice if your models fit within its 16GB and inference volume is moderate.

Frequently Asked Questions

Can the RTX 2000 Ada Generation or RTX A6000 run large language models?

Both can, but the RTX A6000 (48GB) handles larger models without quantization. The RTX 2000 Ada Generation (16GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the RTX 2000 Ada Generation or the RTX A6000?

The RTX A6000 is faster for token generation — its 768 GB/s memory bandwidth vs 224 GB/s on the RTX 2000 Ada Generation is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The RTX A6000 has the advantage at 38.7 TFLOPS vs 12 TFLOPS, making training runs proportionally faster than on the RTX 2000 Ada Generation.

Technical Specifications Comparison

Architecture & Cores

SpecificationRTX 2000 Ada GenerationRTX A6000
ArchitectureAda LovelaceAmpere
CUDA Cores (CUDA Cores / CUDA Cores)2,81610,752

Memory

SpecificationRTX 2000 Ada GenerationRTX A6000
VRAM Capacity16 GB48 GB
Memory TypeGDDR6GDDR6
Memory Bus128-bit384-bit
Bandwidth224 GB/s768 GB/s

Connectivity & Power

SpecificationRTX 2000 Ada GenerationRTX A6000
InterfacePCIe 4.0 x8PCIe 4.0 x16
TDP70 W300 W
ReleasedMar 2023Apr 2021

Workstation

SpecificationRTX 2000 Ada GenerationRTX A6000
FP32 (TFLOPS)12 TFLOPS38.7 TFLOPS
ECCYesYes
NVLinkNoYes
Form factorlow-profiledual-slot