BGE-VL-base
by BAAI
Lightweight vision-language embeddings for image and document retrieval
BAAI/BGE-VL-basemixpeek://image_extractor@v1/baai_bge_vl_base_v1Overview
BGE-VL Base is BAAI's compact vision-language embedding model for image-text retrieval and visual document search. It gives teams a smaller open model option when CLIP-style embeddings are too generic and larger multimodal retrievers are unnecessary.
On Mixpeek, BGE-VL Base can index screenshots, product images, scanned pages, and video keyframes so an agent can retrieve visual evidence with natural-language queries before asking a VLM to reason over the result.
Architecture
Sentence Transformers compatible vision-language embedding model with a compact parameter footprint. It maps visual and text inputs into a shared retrieval space for semantic similarity search.
Mixpeek SDK Integration
import { Mixpeek } from "mixpeek";
const mx = new Mixpeek({ apiKey: "API_KEY" });
// Managed: create a collection over a bucket; Mixpeek runs this model's extractor
const collection = await mx.collections.create({
namespace_id: "my-namespace",
collection_name: "my-collection",
source: { type: "bucket", bucket_ids: ["bkt_your_bucket"] },
feature_extractor: {
feature_extractor_name: "visual_embeddings",
version: "v1",
parameters: { model_id: "BAAI/BGE-VL-base" },
},
});Capabilities
- Image-text retrieval with compact inference cost
- Visual document and screenshot search
- Sentence Transformers integration
- MIT license
Use Cases on Mixpeek
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Specification
Research Paper
BGE-VL Base
arxiv.orgBuild a pipeline with BGE-VL-base
Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.
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