GPU Comparison
Select up to 2 GPUs to analyze their pricing, performance, and specifications side-by-side.
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 $728 EUR cheaper than the Arc Pro B65.
Maximum Capacity Reached. Remove a model to add another. (2/2)
Comparable or lower specs
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 $473 EUR, $728 EUR less than the Arc Pro B65 at $1,202 EUR. 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 ($728 EUR 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?
Which is faster for LLM inference, the Arc Pro B50 or the Arc Pro B65?
Which is better for AI training?
Technical Specifications Comparison
Architecture & Cores
| Specification | Arc Pro B50 | Arc Pro B65 |
|---|---|---|
| Architecture | Xe2-HPG | Xe2-HPG |
| CUDA Cores (Shading Units / Shading Units) | 2,048 | 2,560✓ |
Memory
| Specification | Arc Pro B50 | Arc Pro B65 |
|---|---|---|
| VRAM Capacity | 16 GB | 32 GB✓ |
| Memory Type | GDDR6 | GDDR6 |
| Memory Bus | 128-bit | 256-bit✓ |
| Bandwidth | 224 GB/s | 608 GB/s✓ |
Connectivity & Power
| Specification | Arc Pro B50 | Arc Pro B65 |
|---|---|---|
| Interface | PCIe 5.0 x8 | PCIe 5.0 x16 |
| TDP | 70 W✓ | 200 W |
| Released | Sep 2025 | Mar 2026 |
Workstation
| Specification | Arc Pro B50 | Arc Pro B65 |
|---|---|---|
| FP32 (TFLOPS) | 10.65 TFLOPS | 12.3 TFLOPS✓ |
| ECC | Yes | Yes |
| NVLink | No | No |
| Form factor | low-profile | dual-slot |