3.3 KiB
3.3 KiB
Vision Language Models
These models accept multi-modal inputs (e.g., images and text) and generate text output. They augment language models with visual encoders and require a specific chat template for handling vision prompts.
Example launch Command
python3 -m sglang.launch_server \
--model-path meta-llama/Llama-3.2-11B-Vision-Instruct \ # example HF/local path
--host 0.0.0.0 \
--port 30000 \
Supporting Matrixs
| Model Family (Variants) | Example HuggingFace Identifier | Chat Template | Description |
|---|---|---|---|
| Qwen-VL (Qwen2 series) | Qwen/Qwen2.5-VL-7B-Instruct |
qwen2-vl |
Alibaba’s vision-language extension of Qwen; for example, Qwen2.5-VL (7B and larger variants) can analyze and converse about image content. |
| DeepSeek-VL2 | deepseek-ai/deepseek-vl2 |
deepseek-vl2 |
Vision-language variant of DeepSeek (with a dedicated image processor), enabling advanced multimodal reasoning on image and text inputs. |
| Janus-Pro (1B, 7B) | deepseek-ai/Janus-Pro-7B |
janus-pro |
DeepSeek’s open-source multimodal model capable of both image understanding and generation. Janus-Pro employs a decoupled architecture for separate visual encoding paths, enhancing performance in both tasks. |
| MiniCPM-V / MiniCPM-o | openbmb/MiniCPM-V-2_6 |
minicpmv |
MiniCPM-V (2.6, ~8B) supports image inputs, and MiniCPM-o adds audio/video; these multimodal LLMs are optimized for end-side deployment on mobile/edge devices. |
| Llama 3.2 Vision (11B) | meta-llama/Llama-3.2-11B-Vision-Instruct |
llama_3_vision |
Vision-enabled variant of Llama 3 (11B) that accepts image inputs for visual question answering and other multimodal tasks. |
| LLaVA (v1.5 & v1.6) | e.g. liuhaotian/llava-v1.5-13b |
vicuna_v1.1 |
Open vision-chat models that add an image encoder to LLaMA/Vicuna (e.g. LLaMA2 13B) for following multimodal instruction prompts. |
| LLaVA-NeXT (8B, 72B) | lmms-lab/llava-next-72b |
chatml-llava |
Improved LLaVA models (with an 8B Llama3 version and a 72B version) offering enhanced visual instruction-following and accuracy on multimodal benchmarks. |
| LLaVA-OneVision | lmms-lab/llava-onevision-qwen2-7b-ov |
chatml-llava |
Enhanced LLaVA variant integrating Qwen as the backbone; supports multiple images (and even video frames) as inputs via an OpenAI Vision API-compatible format. |
| Gemma 3 (Multimodal) | google/gemma-3-4b-it |
gemma-it |
Gemma 3’s larger models (4B, 12B, 27B) accept images (each image encoded as 256 tokens) alongside text in a combined 128K-token context. |
| Kimi-VL (A3B) | moonshotai/Kimi-VL-A3B-Instruct |
kimi-vl |
Kimi-VL is a multimodal model that can understand and generate text from images. |