Arc Pro B70 and openclaw

MortchTheAIGuy — Fri, 10 Jul 2026 20:47:03 GMT

Difficulty Using Dual Intel Arc Pro B70 GPUs with OpenClaw and Local AI Models

I recently purchased two Intel Arc Pro B70 GPUs with the intention of using them for local AI inference and agent workloads. Both cards are installed in a Windows 11 system with an Intel Core i5-14600K, and I also use WSL2 with Ubuntu 24.04.

My primary goal was to use the B70 GPUs as the local inference hardware for an OpenClaw agent. Unfortunately, I have been unable to find a stable and straightforward software configuration that allows OpenClaw to reliably use the cards.

The main difficulty appears to be the software stack rather than the hardware itself. OpenClaw generally expects to connect to an inference backend such as Ollama or another OpenAI-compatible local server. NVIDIA hardware has a well-established path through CUDA, but the equivalent workflow for the Arc Pro B70 is much less clear.

I have encountered several practical issues:

It is unclear which Windows or WSL inference backend currently provides reliable support for the Arc Pro B70.
Many local-AI installation guides and OpenClaw examples assume an NVIDIA GPU and CUDA.
Ollama does not appear to offer the same simple or mature Intel GPU workflow that it provides for NVIDIA hardware.
Intel-specific options involving oneAPI, Level Zero, OpenVINO, IPEX-LLM, llama.cpp, or SYCL are difficult to evaluate because support varies between projects, operating systems, GPU generations, and model formats.
Even when a backend can potentially access the GPU, it may not expose the OpenAI-compatible API or model-management features that OpenClaw expects.
Using two B70 cards adds another layer of uncertainty. It is not clear which available inference engines can reliably divide a model between both GPUs or otherwise make effective use of both cards.
Documentation specifically addressing the Arc Pro B70, Windows 11, WSL2, multi-GPU inference, and agent frameworks is currently limited.

At this point, I am considering moving the main OpenClaw inference workload back to an older Ubuntu system containing an NVIDIA RTX 3090 and Ollama. That combination is considerably easier to configure and is already functioning as a local inference endpoint. I would then try to use the two B70 cards for separate worker tasks rather than as the primary OpenClaw “brain.”

I purchased the B70 cards specifically because their memory capacity and professional AI positioning seemed well suited to local models. I would like to continue using them, but I need a clearer supported path.

I would appreciate guidance from Intel or other community members on the following:

What is the recommended inference stack for the Arc Pro B70 on Windows 11 or WSL2?
Is there a supported OpenAI-compatible inference server that works reliably with the B70?
Can two B70 cards currently be used together for a single model, either through tensor parallelism or model layer splitting?
Is native Windows or native Linux currently the better-supported environment?
Are there any official installation guides, validated model lists, containers, or reference configurations for local LLM inference on the B70?
Does Intel have a recommended way to connect an agent framework such as OpenClaw to an Arc Pro inference endpoint?

I am comfortable working with Windows, Linux, WSL, Docker, command-line tools, and local model servers. I am not necessarily looking for a one-click solution, but I would like to know which software path Intel considers stable and supported for these cards.

Any guidance, working configuration examples, or clarification regarding the current state of B70 multi-GPU LLM support would be greatly appreciated.

topic Arc Pro B70 and openclaw in Graphics

Arc Pro B70 and openclaw