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Radeon PRO W6400 vs RTX A2000 6GB

Workstation Verdict

The RTX A2000 6GB has more VRAM (6GB vs 4GB), making it better suited for large models and memory-intensive workloads. Memory bandwidth runs 125% ahead (288 GB/s versus 128 GB/s), which feeds straight through into quicker inference.

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

VS
AMD Radeon
PRO W6400
Price
SEK 2,974βœ“
VRAM
4 GB GDDR6
Mem. Speed
128 GB/s
FP32 Compute
3.6 TFLOPS
Key Specs Advantage

Comparable or lower specs

Price
Reference GPU
VRAM
6 GB GDDR6βœ“
Mem. Speed
288 GB/sβœ“
FP32 Compute
8 TFLOPSβœ“
Key Specs Advantage
+333% CUDA Cores (3,328 vs 768)
+200% Memory Bus (192-bit vs 64-bit)
+125% Bandwidth (288 GB/s vs 128 GB/s)

Radeon PRO W6400 vs RTX A2000 6GB: In-Depth Breakdown

VRAM: Radeon PRO W6400 vs RTX A2000 6GB

The RTX A2000 6GB carries 6GB of VRAM versus 4GB on the Radeon PRO W6400. VRAM capacity is the primary constraint for running AI models without quantization β€” a 70B-parameter model in FP16 requires roughly 140GB, and even smaller models benefit from extra headroom. The 2GB advantage here means the RTX A2000 6GB can run larger models natively and handle bigger batch sizes in production.

Inference Speed: Memory Bandwidth

The rate data moves to the compute units β€” memory bandwidth β€” is what caps autoregressive inference speed (token generation in LLMs). Here the RTX A2000 6GB reaches 288 GB/s against 128 GB/s for the Radeon PRO W6400, a 125% advantage. Once a model is resident in VRAM, token throughput tracks this figure closely, so the RTX A2000 6GB generates tokens proportionally faster on bandwidth-bound workloads.

AI Training & Compute

For model training, scientific simulation, and rendering, FP32 throughput is the key metric. The RTX A2000 6GB delivers 8 TFLOPS against 3.6 TFLOPS for the Radeon PRO W6400 β€” a 122% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX A2000 6GB.

Which should you buy: Radeon PRO W6400 or RTX A2000 6GB?

The RTX A2000 6GB is the stronger choice for large-model workloads where VRAM is the bottleneck. The Radeon PRO W6400 is more economical, and sufficient if your models fit within its 4GB.

Frequently Asked Questions

Can the Radeon PRO W6400 or RTX A2000 6GB run large language models?

Yes, both are capable, though the RTX A2000 6GB (6GB) can handle bigger models without needing quantization. The Radeon PRO W6400 (4GB) is better suited to smaller or more heavily quantized models.

Which is faster for LLM inference, the Radeon PRO W6400 or the RTX A2000 6GB?

The RTX A2000 6GB is faster for token generation β€” its 288 GB/s memory bandwidth vs 128 GB/s on the Radeon PRO W6400 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The RTX A2000 6GB leads at 8 TFLOPS versus 3.6 TFLOPS, so training runs finish proportionally sooner than on the Radeon PRO W6400.

Which should you buy: Radeon PRO W6400 or RTX A2000 6GB?

The RTX A2000 6GB is the stronger choice for large-model workloads where VRAM is the bottleneck. The Radeon PRO W6400 is more economical, and sufficient if your models fit within its 4GB.

Technical Specifications Comparison

Architecture & Cores

Architecture & Cores specifications comparison between Radeon PRO W6400 and RTX A2000 6GB
SpecificationRadeon PRO W6400RTX A2000 6GB
ArchitectureRDNA 2Ampere
CUDA Cores (Stream Processors / CUDA Cores)7683,328βœ“

Memory

Memory specifications comparison between Radeon PRO W6400 and RTX A2000 6GB
SpecificationRadeon PRO W6400RTX A2000 6GB
VRAM Capacity4 GB6 GBβœ“
Memory TypeGDDR6GDDR6
Memory Bus64-bit192-bitβœ“
Bandwidth128 GB/s288 GB/sβœ“

Connectivity & Power

Connectivity & Power specifications comparison between Radeon PRO W6400 and RTX A2000 6GB
SpecificationRadeon PRO W6400RTX A2000 6GB
InterfacePCIe 4.0 x4PCIe 4.0 x16
TDP50 Wβœ“70 W
ReleasedMar 2022Jan 2022

Workstation

Workstation specifications comparison between Radeon PRO W6400 and RTX A2000 6GB
SpecificationRadeon PRO W6400RTX A2000 6GB
FP32 (TFLOPS)3.6 TFLOPS8 TFLOPSβœ“
ECCYesYes
NVLinkNoNo
Form factorlow-profilelow-profile