Qwen3.5

Qwen3.5 is Alibaba's vision-language model family. It accepts an image and a text prompt and returns a text response. Two pretrained checkpoints are available:

Qwen3.5 accuracy

Headline vision-language benchmarks (non-thinking mode) from the official model cards (0.8B, 2B):

Qwen3.5 inference speed

Latency measured with Roboflow Inference on 1x NVIDIA L4, batch size 1, generating exactly 128 tokens with greedy decoding from a fixed prompt. Latency scales with output length, so use tokens/sec to estimate other lengths.

Use Qwen3.5 in a Workflow

Qwen 3.5 VL is available as a preconfigured Workflow on the "Open-Source Models" tab of the Models page. Select "Qwen VL", choose a model variant and prompt, then click "Test API" to fork the Workflow into your Workspace and start running inference.

The Workflow uses the unified qwen_vlm@v1 block, which supports multiple Qwen VL generations:

Qwen3.5 API

export ROBOFLOW_API_KEY="your-key-here"

pip install -U inference-sdk supervision

import os
import supervision as sv
from inference_sdk import InferenceHTTPClient

image = sv.load_image_from_url("https://media.roboflow.com/quickstart/dog.jpeg")

client = InferenceHTTPClient(
    api_url="https://your-deployment.roboflow.cloud",
    api_key=os.environ["ROBOFLOW_API_KEY"],
)
result = client.infer_lmm(
    image,
    model_id="qwen3_5-2b",
    prompt="Describe this image briefly.",
    max_new_tokens=256,
)
print(result["response"])

The code above prints the model response to the terminal:

A person wearing a white t-shirt and red shorts is carrying a black backpack on their shoulder, with a beagle dog perched on top of it. The scene takes place outdoors in a residential area, with modern apartment buildings in the background and greenery along the sidewalk. The person appears to be walking or standing near a building with large windows.

You can train your own Qwen3.5 checkpoint on Roboflow and call it by its per-model {workspace}/{model-slug} ID (see Versions, Trainings, and Models).

Run Qwen3.5 with self-hosted Inference

Qwen3.5 can also be loaded directly with the inference package instead of being called over HTTP.

pip install "inference[transformers]"

from inference.models.qwen3_5vl.qwen3_5vl_inference_models import (
    InferenceModelsQwen35VLAdapter,
)

model = InferenceModelsQwen35VLAdapter(
    model_id="qwen3_5-0.8b",
    api_key="YOUR_API_KEY",
)

image = "https://media.roboflow.com/dog.jpeg"
prompt = "How many dogs are in this image?"

preprocessed, metadata = model.preprocess(image, prompt)
predictions = model.predict(preprocessed)
result = model.postprocess(predictions, metadata)

print(result[0].response)

Qwen3.5 also supports a "thinking" mode, in which the model generates reasoning tokens before answering.

Execution modes in Workflows

When used in a Workflow, Qwen3.5 runs in one of two modes:

• Local execution: the model runs on your Inference server (GPU recommended).
• Remote execution: the model is invoked over HTTP on a remote Inference server.