QDNASales and integration of LLM inference and training platforms, on-premises or hybrid

Serving Qwen 3.6 27B with vLLM

Qwen 3.6 27B has 27 billion parameters. vLLM targets production serving, throughput and concurrency. This page gives the memory required and the platforms that qualify.

Short answer. vLLM serves Qwen 3.6 27B as soon as the machine offers at least 15.5 GB of memory, the weight footprint in NVFP4. 8 of the 8 platforms in the catalogue meet that bar.

What is the minimum memory?

Qwen 3.6 27B totals 27 billion parameters. In NVFP4 its weights take about 15.5 GB including the runtime margin. In FP8 the footprint doubles, to about 31.0 GB. The attention cache sits on top and depends on the context served.

What is vLLM for?

vLLM targets production serving, throughput and concurrency. See the vLLM and Qwen 3.6 27B fact sheets.

On which platforms?

How much memory for Qwen 3.6 27B with vLLM?

About 15.5 GB in NVFP4 for the weights, excluding the attention cache.

Does vLLM suit Qwen 3.6 27B?

vLLM serves Qwen 3.6 27B as soon as the machine offers at least 15.5 GB of memory, the weight footprint in NVFP4. 8 of the 8 platforms in the catalogue meet that bar.

Method

Parameter counts and memory figures come from the site fact sheets. Memory footprints are calculated, not measured: a reading on real hardware may differ depending on the engine and the exact weight format. Prices are indicative and not contractual.