Intel Arc Pro B70 Outclasses NVIDIA’s RTX Pro 4000 In AI At Half The Cost, 33% More Memory

Intel's Arc Pro B70 is designed to offer accessible local inference for AI users, delivering more memory at half the price of the competition.

Intel Arc Pro B70 vs NVIDIA RTX PRO 4000 Blackwell: 32 GB vs 24 GB, $949 vs $1800, More AI Context, 2x Tokens Per Dollar

So we talked about the unveiling of the Intel Arc Pro B70 graphics card in our other post, where we highlighted the specifications, availability, and prices of the product. The B70 is going to be the flagship Pro & AI product from Intel within its Arc Pro stack, and they have some interesting figures to showcase for this product.

On a high-level, Intel states the following benefits for its Arc Pro B70 graphics cards:

• Up to 2.2x larger context windows with the Intel Arc Pro B70 versus the competition.
• Up to 6.2x faster responses in multi-agent/multi-user workloads with the Intel Arc Pro B70 versus the competition.
• Up to 2x tokens per dollar performance with the Intel Arc Pro B70 versus the competition.

First of all, the Intel Arc Pro B70 looks very impressive given its specifications at this price point. Intel has positioned the Arc Pro B70 against the NVIDIA RTX PRO 4000 Blackwell. That GPU generally costs around $1800 US, which is almost twice the price of the Arc Pro B70, which starts at $949 US. One of the main advantages is very clear, and that's memory. The RTX Pro features 24 GB of memory, but the Arc Pro B70 has 32 GB of memory, a 33% higher capacity.

This 32 GB memory is crucial for AI, as more memory means more AI context. In the first benchmark test, Intel showcases the Token Throughput vs Context Length of these cards. The model being used is Llama 3.1 8b, and BF16 is being leveraged. The RTX PRO 4000 supports a context length of 42K before it goes out of memory. Meanwhile, the Arc Pro B70 supports a context length of up to 93K before its memory is exhausted. That's up to a 2.2x larger context window.

Next up, Intel offers a look at multi-agent flows in parallel. Here, the model being used is Ministral Instruct 2410 8B (BF16), and you can see that the B70 offers up to a 85% higher token throughput for multiple users/requests versus the NVIDIA RTX PRO 4000 in the Linux OS. Arc Pro delivers much higher throughput than NVIDIA's Blackwell offering at half the cost.

Intel Arc Pro B60 also delivers much quicker answers for multiple users with a faster time to first token versus the competition. Here, the leading is extended up to 6.2x, which is impressive. Do note that all of this isn't just the hardware working; it's also Intel's own oneAPI and AI software stack that is working to deliver faster throughput.

This capability further shows in the scalable multi-GPU software stack, which enables support for multiple GPUs, opening up the space for larger models and contexts in multi-GPU setups.

The Intel Arc Pro B70 enables up to 183K context window in DS-R1-Distill-Qwen 3 32B (Int4) versus 80K for RTX PRO 4000, a 304K context window in Qwen3 32B (FP8) versus 199K for RTX PRO 4000, and 408K context window in Mistral-Small 24B (BF16) versus 243K for the RTX PRO 4000. These tests were run on a 4-GPU solution for both Intel and NVIDIA.

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Moving forward, Intel showcases up to 2x tokens per dollar for its Arc Pro B70 GPUs in single, dual, and quad GPU systems. So the performance is very scalable and is perfect for users running a single entry-level workstation or a high-end multi-GPU stack.

So overall, a very positive showcase of Intel's brand new AI powerhouse, and that too at a cost that will be very attractive for AI & Pro users. It looks like the next few months will be very interesting as the Arc Pro B70 & the cost-effective B65 roll out on retail shelves. The question remains, though, whether we will see a gaming-oriented variant of Big Battlemage, maybe something like the Radeon VII, which housed a GPU that was built for Pro users but landed as a gaming-oriented graphics card as a niche enthusiast product.

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