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Arc Pro B50 vs Arc Pro B60

Workstation Verdict

The Arc Pro B60 has more VRAM (24GB vs 16GB), making it better suited for large models and memory-intensive workloads. Memory bandwidth runs 104% ahead (456 GB/s versus 224 GB/s), which feeds straight through into quicker inference.

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

INTEL Arc
Pro B60
Price
Reference GPU
VRAM
24 GB GDDR6✓
Mem. Speed
456 GB/s✓
FP32 Compute
12.29 TFLOPS✓
Key Specs Advantage
+104% Bandwidth (456 GB/s vs 224 GB/s)
+50% Memory Bus (192-bit vs 128-bit)
+25% Shading Units (2,560 vs 2,048)

Arc Pro B50 vs Arc Pro B60: In-Depth Breakdown

VRAM: Arc Pro B50 vs Arc Pro B60

The Arc Pro B60 carries 24GB 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 8GB advantage here means the Arc Pro B60 can run larger models natively and handle bigger batch sizes in production.

Inference Speed: Memory Bandwidth

The rate data moves to the compute units — memory bandwidth — is what caps autoregressive inference speed (token generation in LLMs). Here the Arc Pro B60 reaches 456 GB/s against 224 GB/s for the Arc Pro B50, a 104% advantage. Once a model is resident in VRAM, token throughput tracks this figure closely, so the Arc Pro B60 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 Arc Pro B60 delivers 12.29 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 B60.

Which should you buy: Arc Pro B50 or Arc Pro B60?

The Arc Pro B60 is the stronger choice for large-model workloads where VRAM is the bottleneck. The Arc Pro B50 is more economical, and sufficient if your models fit within its 16GB.

Frequently Asked Questions

Can the Arc Pro B50 or Arc Pro B60 run large language models?

Yes, both are capable, though the Arc Pro B60 (24GB) can handle bigger models without needing quantization. The Arc Pro B50 (16GB) is better suited to smaller or more heavily quantized models.

Which is faster for LLM inference, the Arc Pro B50 or the Arc Pro B60?

The Arc Pro B60 is faster for token generation — its 456 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 B60 leads at 12.29 TFLOPS versus 10.65 TFLOPS, so training runs finish proportionally sooner than on the Arc Pro B50.

Which should you buy: Arc Pro B50 or Arc Pro B60?

The Arc Pro B60 is the stronger choice for large-model workloads where VRAM is the bottleneck. The Arc Pro B50 is more economical, and sufficient if your models fit within its 16GB.

Technical Specifications Comparison

Architecture & Cores

Architecture & Cores specifications comparison between Arc Pro B50 and Arc Pro B60
SpecificationArc Pro B50Arc Pro B60
ArchitectureXe2-HPGXe2-HPG
CUDA Cores (Shading Units / Shading Units)2,0482,560✓

Memory

Memory specifications comparison between Arc Pro B50 and Arc Pro B60
SpecificationArc Pro B50Arc Pro B60
VRAM Capacity16 GB24 GB✓
Memory TypeGDDR6GDDR6
Memory Bus128-bit192-bit✓
Bandwidth224 GB/s456 GB/s✓

Connectivity & Power

Connectivity & Power specifications comparison between Arc Pro B50 and Arc Pro B60
SpecificationArc Pro B50Arc Pro B60
InterfacePCIe 5.0 x8PCIe 5.0 x8
TDP70 W✓200 W
ReleasedSep 2025Jan 2025

Workstation

Workstation specifications comparison between Arc Pro B50 and Arc Pro B60
SpecificationArc Pro B50Arc Pro B60
FP32 (TFLOPS)10.65 TFLOPS12.29 TFLOPS✓
ECCYesYes
NVLinkNoNo
Form factorlow-profiledual-slot