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Arc Pro B50 vs Arc Pro B65

Workstation Verdict

With 32GB on board versus 16GB for the Arc Pro B50, the Arc Pro B65 carries more headroom for large models and memory-hungry workloads. Its memory bandwidth is 171% higher (608 GB/s vs 224 GB/s), translating directly to faster inference throughput.

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

VS
INTEL Arc
Pro B50
Price
Reference GPU
VRAM
16 GB GDDR6
Mem. Speed
224 GB/s
FP32 Compute
10.65 TFLOPS
Key Specs Advantage

Comparable or lower specs

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

VRAM: Arc Pro B50 vs Arc Pro B65

With 32GB of VRAM against the Arc Pro B50's 16GB, the Arc Pro B65 has a 16GB edge. VRAM is what determines whether a model fits without quantization at all — a 70B-parameter model in FP16 needs around 140GB, and smaller models still benefit from spare capacity. That extra headroom lets the Arc Pro B65 load bigger models and run larger production batch sizes.

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

FP32 throughput is the metric that matters most for training, scientific simulation, and rendering work. The Arc Pro B65 posts 12.3 TFLOPS versus 10.65 TFLOPS on the Arc Pro B50, a 15% compute lead. Expect training jobs and heavy matrix math to finish proportionally sooner on the Arc Pro B65.

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

For large-model workloads bottlenecked on VRAM, the Arc Pro B65 is the better pick. The Arc Pro B50 costs less and holds up fine if your models fit inside its 16GB.

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 generates tokens faster: its 608 GB/s of memory bandwidth against 224 GB/s on the Arc Pro B50 is the main factor behind 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.

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

For large-model workloads bottlenecked on VRAM, the Arc Pro B65 is the better pick. The Arc Pro B50 costs less and holds up fine if your models fit inside its 16GB.

Technical Specifications Comparison

Architecture & Cores

Architecture & Cores specifications comparison between Arc Pro B50 and Arc Pro B65
SpecificationArc Pro B50Arc Pro B65
ArchitectureXe2-HPGXe2-HPG
CUDA Cores (Shading Units / Shading Units)2,0482,560

Memory

Memory specifications comparison between Arc Pro B50 and Arc Pro B65
SpecificationArc Pro B50Arc Pro B65
VRAM Capacity16 GB32 GB
Memory TypeGDDR6GDDR6
Memory Bus128-bit256-bit
Bandwidth224 GB/s608 GB/s

Connectivity & Power

Connectivity & Power specifications comparison between Arc Pro B50 and Arc Pro B65
SpecificationArc Pro B50Arc Pro B65
InterfacePCIe 5.0 x8PCIe 5.0 x16
TDP70 W200 W
ReleasedSep 2025Mar 2026

Workstation

Workstation specifications comparison between Arc Pro B50 and Arc Pro B65
SpecificationArc Pro B50Arc Pro B65
FP32 (TFLOPS)10.65 TFLOPS12.3 TFLOPS
ECCYesYes
NVLinkNoNo
Form factorlow-profiledual-slot