Intel Battlemage GPUs Arrive with ARC Pro B65 and B70 Featuring 32GB Memory

Intel expands Battlemage lineup with Arc Pro GPUs targeting AI workloads and high memory capacity use cases.

Hardware by Godrics01 on Apr 02, 2026

ARC Pro B65 and B70 are the first Intel Battlemage GPUs. The specification documents for both models include important hardware information and its location. The microarchitecture is called XC2 and is based on TSMC's N5 process.

There are signs that access to newer nodes, such as N3, may be constrained, suggesting that future GPU production may occur in-house.

Intel Battlemage GPUs, Arrive with ARC Pro B65 and B70, Featuring 32GB Memory, NoobFeed

Differences in Core Specifications and Performance

B65 has 20 Xe cores, but the B70 has 32. This fits with what people thought a higher-end configuration would look like, perhaps comparable to a B770-class device rumored to be in the works. Still, it wasn't released as a consumer card. Both versions have 20 or 32 ray tracing units, and the B65 has a vector engine rated at 160, while the B70 has a rating of 250.

We can see that the B70 is much more powerful because it has faster clocks and a bigger overall setup. You should expect a big difference between the two in terms of computing power.

Setting up Memory and the Interface

Both GPUs have a PCIe Gen5x16 interface and a 256-bit memory bus. Each card has 32GB of GDDR6 memory. That much power is a lot for a GPU in this price range, especially one that costs less than $1000.

We should consider how important memory capacity is based on the job to be done. In some cases, having 32GB of space available can be more useful than just having fast speed.

AI Workloads with Real-Life Examples

Intel seems to be focusing on AI and home lab settings. These GPUs are meant to help developers and techies become used to Arc hardware, especially for AI-related work. That familiarity could lead people to use Intel's data center accelerators for a long time.

There are two key parts to memory needs: training and inference. Memory speed is critical for training workloads, which is why high-end accelerators use HBM that is near the die. When it comes to inference workloads, capacity is increasingly important. You need enough RAM to hold the entire model; otherwise, performance drops significantly when it has to switch to storage.

Intel Battlemage GPUs, Arrive with ARC Pro B65 and B70, Featuring 32GB Memory, NoobFeed

Expectations for Bandwidth and Real-World Performance

The total memory bandwidth ranges from 608 GB/s to 660 GB/s. This isn't the best in the business, but it's good enough when you add 32GB of RAM. You will see that this level of bandwidth is enough for home labs, where workloads are not as big as those in industry.

We can predict that faster memory might make inference a little faster, but not enough capacity will cause performance to drop much more. These GPUs are useful for local AI applications since they have enough memory to bypass that bottleneck.

Final Thoughts

Intel's continual GPU releases show that the company is still investing in this area. That presence is vital for keeping the competition going. The Arc Pro B65 and B70 are more focused on development ecosystems and workloads that require a lot of space than on gaming performance alone.

You can tell that the plan isn't just about getting good results right away; it's also about getting people used to Intel's GPU stack over time.

Also, check our other hardware articles: