Status: Official — Intel published this on Oct 16, 2026 (source: github.com).

Intel

Company · 2 updates

Where it stands

As of Oct 16, Intel's llm-scaler-vllm PV release 1.5 (Docker image intel/llm-scaler-vllm:1.5) upgrades its Intel XPU build from vLLM 0.14.0 to a 0.26.0 baseline and PyTorch 2.10 to 2.12.

Timeline · newest first

Oct 16
Official
Intel LLM-Scaler-vLLM 1.5 moves to vLLM 0.26 and adds Qwen3.8, Gemma 4, FP8 and MTP support on Intel GPUs
Intel published this on Oct 16, 2026 (source: github.com).
Intel's llm-scaler-vllm PV release 1.5 (Docker image intel/llm-scaler-vllm:1.5) upgrades its Intel XPU build from vLLM 0.14.0 to a 0.26.0 baseline and PyTorch 2.10 to 2.12. It adds Qwen3.6-27B, Qwen3.8-27B, Qwen3.6-35B-A3B and Gemma 4 26B-A4B and 31B, online FP8 and symmetric INT4 quantization, FP8 KV cache, MTP and LoRA serving, and DFlash for several models. Intel lists faster time to first token for Qwen and Gemma 4 and fixes for prefix caching with MTP and block-FP8 corruption under concurrent decoding.
Source: Intel
Oct 12
Reported by Reuters
Intel CEO Lip-Bu Tan says Chinese frontier AI models are cheaper per token and being adopted 'very fast', per Reuters
Not confirmed by the company — reported on Oct 12, 2026 (source: money.usnews.com).
Speaking at a DBS panel in Singapore, Intel CEO Lip-Bu Tan said token costs of Chinese frontier models have been lower and adoption has been "very fast," calling models such as DeepSeek, Kimi and GLM "good enough." He said he is a strong believer in open source as the best way to drive efficiency, that markets will decide which models suit which uses, and that quantum computing could go mainstream in three to five years.
Source: Reuters

Intel

Where it stands

Intel LLM-Scaler-vLLM 1.5 moves to vLLM 0.26 and adds Qwen3.8, Gemma 4, FP8 and MTP support on Intel GPUs

Intel CEO Lip-Bu Tan says Chinese frontier AI models are cheaper per token and being adopted 'very fast', per Reuters