Intel LLM-Scaler-vLLM 1.5: more up-to-date inference on Intel Arc GPUs
On October 16, 2026, Intel released version 1.5 of LLM-Scaler-vLLM, a Docker stack with vLLM for Intel Arc GPUs, which jumped from vLLM 0.14 to 0.26 and added more models and FP8 quantization.
Source: Intel LLM-Scaler-vLLM PV 1.5 Brings Big Improvements (phoronix.com). Text prepared with AI from this source.
What happened and what to do
According to Phoronix, the release brings PyTorch 2.12, support for more Qwen and Gemma 4 models, online FP8 and symmetric INT4 quantization and FP8 KV cache, plus faster time to first token and improvements in MTP decoding and LoRA serving. Upstream vLLM is already at 0.31, so Intel's stack still lags behind.
For teams that want to serve open models without relying only on NVIDIA GPUs, Intel's stack becomes more viable. Compare cost per token and stability with your models before changing hardware.
How the consultancy can help
Wendelmaques can, on demand, test your models on LLM-Scaler-vLLM, compare cost and performance with your current infrastructure and set up operations with monitoring if the switch pays off.
Next step
If GPU cost weighs on your AI operation, send a short description of your models and volume and receive a scoped proposal.
Let's assess your project
I reply with scope and a proposal.