# Qwen/Qwen3-14B — vLLM serving recipe

> Qwen3 14B dense model with hybrid thinking/non-thinking modes, validated for Intel Xeon 6 CPU serving.

Configuration: hardware `xeon6` (4× Xeon 6) · strategy `single_node_tp` (Tensor Parallel) · variant `default` (BF16) · features `tool_calling`

- Interactive page: https://vllm-recipes-git-preview-vllm-pr-60762-inferact-inc.vercel.app/Qwen/Qwen3-14B
- This configuration as JSON: https://vllm-recipes-git-preview-vllm-pr-60762-inferact-inc.vercel.app/Qwen/Qwen3-14B.json?hardware=xeon6

The commands below were rendered for exactly this configuration and take precedence over any example in the guide.

## Other configurations

Change the query string (the same parameters as the page URL) and fetch this URL again. Unknown or incompatible values fall back to the recipe default, so check the Configuration line.

- `hardware`: `xeon6`
- `variant`: `default`, `fp8`, `awq`
- `strategy`: `single_node_tp`, `multi_node_tp` (multi-node strategies also need `nodes=<n>`)
- `features`: comma-separated list of `tool_calling`, `reasoning`, `long_context` (default: `tool_calling`)

## Install

Requires vLLM >= 0.8.5.

Docker image: `vllm/vllm-openai-cpu:latest-x86_64`

## Serve

```bash
vllm serve Qwen/Qwen3-14B \
  --tensor-parallel-size 1 \
  --enable-auto-tool-choice \
  --tool-call-parser hermes
```

Docker equivalent:

```bash
docker run --shm-size=16g \
  --privileged --ipc=host -p 8000:8000 \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  vllm/vllm-openai-cpu:latest-x86_64 Qwen/Qwen3-14B \
  --tensor-parallel-size 1 \
  --enable-auto-tool-choice \
  --tool-call-parser hermes
```

## Guide

> Background reference. Commands in it are examples and may target another configuration — use the Serve section above.

### Overview

Qwen3-14B is a Qwen3 dense model with hybrid thinking and non-thinking modes.
Intel Xeon 6 CPU serving was validated with BF16.

### Prerequisites

- Hardware: Intel Xeon 6 CPUs
- vLLM >= 0.8.5

#### pip (Intel Xeon 6 CPUs)

Follow the [CPU pre-built wheels](https://docs.vllm.ai/en/latest/getting_started/installation/cpu/#pre-built-wheels)
installation instructions.

#### Docker (Intel Xeon 6 CPUs)

```bash
docker pull vllm/vllm-openai-cpu:latest-x86_64
```

### Intel Xeon 6

Choose tensor parallelism based on the system topology; the recipe does not
prescribe a fixed TP/DP layout or hard-code NUMA node IDs.

```bash
vllm serve Qwen/Qwen3-14B
```

Docker:

```bash
docker run \
  --privileged --ipc=host -p 8000:8000 \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  vllm/vllm-openai-cpu:latest-x86_64 Qwen/Qwen3-14B \
  --tensor-parallel-size 1 \
  --enable-auto-tool-choice \
  --tool-call-parser hermes
```

### Configuration Notes

- TP/DP values and explicit CPU bindings are intentionally not prescribed.
- The `qwen3` reasoning parser is available in vLLM 0.9.0 and later.

### Runtime and Platform Tuning

The following settings are intentionally not prescribed as portable CPU model
defaults because they depend on the workload, hardware, or runtime environment:

- `--max-num-batched-tokens`: scheduler/throughput tuning.
- `--max-num-seqs`: concurrency and scheduler-capacity tuning.
- `--gpu-memory-utilization`: platform memory-budget tuning.
- `--no-enable-prefix-caching`: workload/benchmark cache-policy tuning.
- `VLLM_ENGINE_ITERATION_TIMEOUT_S`: operational runtime timeout.

These settings may still appear in validated hardware-specific overrides. Tune
them at deployment time based on platform resources, workload shape, and
latency/throughput goals.

### References

- [Model card](https://huggingface.co/Qwen/Qwen3-14B)
- [vLLM CPU installation](https://docs.vllm.ai/en/latest/getting_started/installation/cpu/)