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Cataloged from furiosa-ai/Qwen3-VL-2B-Instruct
All models by furiosa-ai →This repository contains Qwen/Qwen3-VL-2B-Instruct together with a Furiosa Executable Bundle (FXB) for running it on FuriosaAI RNGD with Furiosa-LLM. The same model also runs on other frameworks (such as vLLM, SGLang, and Transformers); for usage with those, see the upstream Qwen/Qwen3-VL-2B-Instruct model card.
Qwen3-VL-2B-Instruct is a 2-billion-parameter dense vision-language model from the Qwen3-VL series. It pairs a vision encoder with a dense transformer decoder, using Interleaved-MRoPE positional embeddings and DeepStack multi-level feature fusion to handle images and videos alongside text. The model covers visual understanding tasks such as OCR, document and chart analysis, spatial reasoning, and video comprehension, and it natively supports tool (function) calling. This is the Instruct (non-thinking) edition. Its intended use is the same as the upstream Qwen/Qwen3-VL-2B-Instruct, released under the Apache 2.0 License.
No quantization is applied — the model runs in the same precision as the upstream weights.
image_url content parts alongside text.hermes tool-call parser.On RNGD, Qwen3-VL-2B-Instruct runs with a tensor-parallel size of 8 PEs, which maps to a single RNGD card (8 PEs per card).
To run this model with Furiosa-LLM, follow the example commands below after installing Furiosa-LLM and its prerequisites.
The simplest way to serve the model is:
To also enable tool (function) calling, add the hermes tool-call parser (the
parser used by the Qwen3 series):
When the server is ready, you will see:
The server exposes an OpenAI-compatible API. You can send a text-only request
with curl:
To ask about an image, pass an image_url content part in the message:
The image_url.url field accepts a remote http:///https:// URL, an inline
base64 data: URL, or a local file:// path (the last requires the
--allowed-local-media-path flag described under Advanced Usage).
Multimodal serving options. furiosa-llm serve provides flags to control
multimodal behavior; requests that violate them are rejected with HTTP 400:
--image-limit-per-prompt N / --video-limit-per-prompt N — maximum number of images/videos allowed per request (default: unlimited).--allowed-local-media-path PATH — allow file:// URLs whose resolved path is under PATH. Local file access is disabled unless this is set.--allowed-media-domains D [D ...] — whitelist of remote domains for SSRF protection. When set, only images from the listed domains are fetched.--interleave-mm-strings — keep image placeholders at their original positions when the model uses a string-format chat template (no-op for OpenAI-format templates, the common case).--mm-processor-cache-gb GB — size of the UUID-keyed multimodal processor cache (default: 4.0). Clients can tag an image_url part with a uuid field and re-reference it in follow-up requests without re-uploading the image bytes; set to 0 to disable.For example, to serve local images under /srv/media and restrict remote
fetches to a single domain:
See the Vision-Language Models guide for image input formats, the UUID cache, and Python client examples.
Tool calling. With the server launched using
--enable-auto-tool-choice --tool-call-parser hermes (see
Launch the server), pass tools in the request and let the
model decide when to call them. See the
Tool Calling guide
for a complete client example and details on tool-choice options.
furiosa-llm serve) — full OpenAI-compatible API reference and serving options# Launch the server, listening on port 8000 by defaultfuriosa-llm serve furiosa-ai/Qwen3-VL-2B-Instructfuriosa-llm serve furiosa-ai/Qwen3-VL-2B-Instruct \ --enable-auto-tool-choice \ --tool-call-parser hermesINFO: Started server process [27507]INFO: Waiting for application startup.INFO: Application startup complete.INFO: Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)curl http://localhost:8000/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "furiosa-ai/Qwen3-VL-2B-Instruct", "messages": [{"role": "user", "content": "What is the capital of France?"}] }' \ | python -m json.toolcurl http://localhost:8000/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "furiosa-ai/Qwen3-VL-2B-Instruct", "messages": [{ "role": "user", "content": [ {"type": "image_url", "image_url": {"url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg"}}, {"type": "text", "text": "Describe this image."} ] }] }' \ | python -m json.toolfuriosa-llm serve furiosa-ai/Qwen3-VL-2B-Instruct \ --allowed-local-media-path /srv/media \ --allowed-media-domains cdn.example.com \ --image-limit-per-prompt 4