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vLLM/recipes/models/Qwen/Qwen3.5-0.8B.yaml
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meta:
title: "Qwen3.5-0.8B"
slug: "qwen3.5-0.8b"
provider: "Qwen"
description: "Qwen3.5 tiny dense multimodal model (0.8B) — ultra-low-VRAM / edge serving with 262K context"
date_added: 2026-04-22
date_updated: 2026-09-14
tasks:
- multimodal
- text
performance_headline: "Tiny Qwen3.5 dense for edge / draft-model use"
related_recipes:
- "Qwen/Qwen3.5-2B"
hardware:
arc_pro_b60: verified
arc_pro_b70: verified
model:
model_id: "Qwen/Qwen3.5-0.8B"
min_vllm_version: "0.17.0"
default_frontend: rust
architecture: dense
parameter_count: "0.8B"
active_parameters: "0.8B"
context_length: 262144
base_args:
- "--trust-remote-code"
base_env: {}
features:
tool_calling:
description: "Enable automatic tool choice with Qwen3 Coder parser"
args:
- "--enable-auto-tool-choice"
- "--tool-call-parser"
- "qwen3_coder"
reasoning:
description: "Enable chain-of-thought reasoning with Qwen3 parser"
args:
- "--reasoning-parser"
- "qwen3"
text_only:
description: "Skip loading the vision encoder for text-only workloads."
args:
- "--language-model-only"
opt_in_features:
- text_only
variants:
default:
precision: bf16
vram_minimum_gb: 2
description: "Full precision BF16 — runs on any modern GPU"
compatible_strategies:
- single_node_tp
hardware_overrides:
xpu:
extra_args:
- "--enforce-eager"
strategy_overrides: {}
guide: |
## Overview
[Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) is the smallest
member of the Qwen3.5 family — same hybrid gated delta networks architecture
and 262K context, at a size suited to edge devices or as a draft model for
speculative decoding with larger Qwen3.5 checkpoints.
## Prerequisites
- **vLLM version:** >= 0.17.0
- **Hardware:** any modern GPU (>=4 GB VRAM) or Intel Arc Pro B60/B70
### Install vLLM
```bash
uv venv
source .venv/bin/activate
uv pip install -U vllm --torch-backend=auto
```
### Docker
```bash
docker pull vllm/vllm-openai-xpu:latest # Intel XPU (B60 / B70)
```
## Launching the Server
```bash
vllm serve Qwen/Qwen3.5-0.8B \
--max-model-len 262144 \
--reasoning-parser qwen3
```
### Docker (Intel XPU B60 / B70)
Validated on 1× Intel Arc Pro B60 / B70 (B60 24 GB, B70 32 GB per card) with the
official vLLM XPU image `vllm/vllm-openai-xpu:latest`.
```bash
docker run --device /dev/dri \
-v /dev/dri/by-path:/dev/dri/by-path --shm-size=16g \
--privileged --ipc=host -p 8000:8000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
vllm/vllm-openai-xpu:latest \
Qwen/Qwen3.5-0.8B \
--reasoning-parser qwen3 \
--enforce-eager
```
## Client Usage
```python
from openai import OpenAI
client = OpenAI(api_key="EMPTY", base_url="http://localhost:8000/v1")
resp = client.chat.completions.create(
model="Qwen/Qwen3.5-0.8B",
messages=[{"role": "user", "content": "Hi!"}],
max_tokens=64,
)
print(resp.choices[0].message.content)
```
## References
- [Model card](https://huggingface.co/Qwen/Qwen3.5-0.8B)
- [Base checkpoint](https://huggingface.co/Qwen/Qwen3.5-0.8B-Base)