Skip to content

GPU Comparison

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

Workstation Verdict

The Arc Pro B65 has more VRAM (32GB vs 16GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 171% higher (608 GB/s vs 224 GB/s), translating directly to faster inference throughput. The Arc Pro B50 is $730 CAD cheaper than the Arc Pro B65.

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

VS
Intel
Arc Pro B50
Price
$570 CAD✓
VRAM
16 GB GDDR6
Mem. Speed
224 GB/s
FP32 Compute
10.65 TFLOPS
Key Specs Advantage

Comparable or lower specs

Intel
Arc Pro B65
Price
$1,300 CAD
VRAM
32 GB GDDR6✓
Mem. Speed
608 GB/s✓
FP32 Compute
12.3 TFLOPS✓
Key Specs Advantage
+171% Bandwidth (608 GB/s vs 224 GB/s)
+100% Memory Bus (256-bit vs 128-bit)
+25% Shading Units (2,560 vs 2,048)
Skip to Spec Sheets ↓

Arc Pro B50 vs Arc Pro B65: In-Depth Breakdown

VRAM: Arc Pro B50 vs Arc Pro B65

The Arc Pro B65 carries 32GB of VRAM versus 16GB on the Arc Pro B50. 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 16GB advantage here means the Arc Pro B65 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 Arc Pro B65 delivers 608 GB/s versus 224 GB/s on the Arc Pro B50, a 171% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the Arc Pro B65 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 Arc Pro B65 delivers 12.3 TFLOPS against 10.65 TFLOPS for the Arc Pro B50 — a 15% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Arc Pro B65.

Price & Value

The Arc Pro B50 lists from $570 CAD, $730 CAD less than the Arc Pro B65 at $1,300 CAD. For budget-constrained teams, the savings may outweigh the spec gap — especially if the smaller card covers your typical workload.

Which should you buy: Arc Pro B50 or Arc Pro B65?

Choose the Arc Pro B65 for maximum capacity — it leads on VRAM, bandwidth, and compute, making it the better fit for large models and training jobs. The Arc Pro B50 is the more budget-friendly option ($730 CAD less) — a solid choice if your models fit within its 16GB and inference volume is moderate.

Frequently Asked Questions

Can the Arc Pro B50 or Arc Pro B65 run large language models?

Both can, but the Arc Pro B65 (32GB) handles larger models without quantization. The Arc Pro B50 (16GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Arc Pro B50 or the Arc Pro B65?

The Arc Pro B65 is faster for token generation — its 608 GB/s memory bandwidth vs 224 GB/s on the Arc Pro B50 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The Arc Pro B65 has the advantage at 12.3 TFLOPS vs 10.65 TFLOPS, making training runs proportionally faster than on the Arc Pro B50.

Technical Specifications Comparison

Architecture & Cores

SpecificationArc Pro B50Arc Pro B65
ArchitectureXe2-HPGXe2-HPG
CUDA Cores (Shading Units / Shading Units)2,0482,560✓

Memory

SpecificationArc Pro B50Arc Pro B65
VRAM Capacity16 GB32 GB✓
Memory TypeGDDR6GDDR6
Memory Bus128-bit256-bit✓
Bandwidth224 GB/s608 GB/s✓

Connectivity & Power

SpecificationArc Pro B50Arc Pro B65
InterfacePCIe 5.0 x8PCIe 5.0 x16
TDP70 W✓200 W
ReleasedSep 2025Mar 2026

Workstation

SpecificationArc Pro B50Arc Pro B65
FP32 (TFLOPS)10.65 TFLOPS12.3 TFLOPS✓
ECCYesYes
NVLinkNoNo
Form factorlow-profiledual-slot
Back to Top ↑