Intel Launches Arc Pro B70 and B65 GPUs with 32GB Memory for AI Inference and Professional Applications
Key Takeaways
- ▸Arc Pro B70 offers 32GB memory and 608 GB/s bandwidth at $949, undercutting Nvidia RTX Pro 4000 ($1,800) and AMD Radeon AI Pro R9700 ($1,299)
- ▸High memory capacity enables efficient local LLM inference with larger context windows and supports multi-GPU scaling for enterprise deployments
- ▸Arc Pro B65 provides a lower-compute option (20 Xe Cores vs 32 on B70) while maintaining the same 32GB memory for cost-conscious professional users
Summary
Intel has introduced two new Battlemage-based GPUs designed for professional applications and local AI inference workloads. The Arc Pro B70 features 32 Xe Cores running at 2800 MHz with 22.9 TFLOPS of FP32 compute performance, paired with 32GB of GDDR6 memory and 608 GB/s bandwidth, starting at $949. The Arc Pro B65 shares the same 32GB memory and bandwidth specifications but with reduced compute capacity (20 Xe Cores), targeting users who need higher memory capacity without maximum performance. Both cards are positioned as more cost-effective alternatives to Nvidia's RTX Pro 4000 ($1,800) and AMD's Radeon AI Pro R9700 ($1,299), making them particularly attractive for organizations looking to deploy multiple GPUs for scaled LLM inference. Intel emphasizes the cards' advantages in larger context window support and lower cost-per-token metrics, while also supporting multi-GPU scaling across its software stack.
- Flexible power envelope (160W-290W) supports diverse system form factors and cooling designs; partner cards available from ARKN, ASRock, Gunnir, Maxsun, and Sparkle
Editorial Opinion
Intel's Arc Pro B70 represents a compelling value proposition in the professional GPU market, particularly for organizations deploying local LLM inference at scale. The aggressive $949 price point with 32GB memory positions it well against premium alternatives, though potential buyers should note Intel's XMX matrix acceleration limitations to FP16/INT8 compared to Nvidia's broader precision support. The dual-card strategy (B70/B65) smartly segments the market between compute-intensive and memory-intensive workloads, though Nvidia's broader product portfolio may still offer more granular optimization options for specific use cases.
