Qwen3-VL

Qwen3-VL

Alibaba
+
+

Related Products

  • LM-Kit.NET
    29 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    1,161 Ratings
    Visit Website
  • LTX
    182 Ratings
    Visit Website
  • Google AI Studio
    41 Ratings
    Visit Website
  • RaimaDB
    12 Ratings
    Visit Website
  • Google Cloud Speech-to-Text
    443 Ratings
    Visit Website
  • Haast
    4 Ratings
    Visit Website
  • 4K Video Downloader
    13,127 Ratings
    Visit Website
  • LALAL.AI
    5,355 Ratings
    Visit Website
  • Planview AdaptiveWork
    718 Ratings
    Visit Website

About

EmbeddingGemma 2 is an open, lightweight multimodal embedding model designed to map text, code, images, video, and audio into a shared embedding space for search, retrieval, classification, routing, and RAG applications. Built on the Gemma 4 architecture and released under the Apache 2.0 license, it has 740 million parameters and is optimized for on-device inference. Its modular design can use as little as 270M parameters for text-only workloads, with optional vision and audio encoders for full multimodal support. Matryoshka Representation Learning lets developers reduce output vectors from 768 dimensions to 512, 256, or 128, lowering storage and memory requirements for local vector databases. The model supports an 8K-token context window and can process up to 5.5 minutes of audio, 29 images, 58 video frames, or interleaved combinations on local hardware.

About

Qwen3-VL is the newest vision-language model in the Qwen family (by Alibaba Cloud), designed to fuse powerful text understanding/generation with advanced visual and video comprehension into one unified multimodal model. It accepts inputs in mixed modalities, text, images, and video, and handles long, interleaved contexts natively (up to 256 K tokens, with extensibility beyond). Qwen3-VL delivers major advances in spatial reasoning, visual perception, and multimodal reasoning; the model architecture incorporates several innovations such as Interleaved-MRoPE (for robust spatio-temporal positional encoding), DeepStack (to leverage multi-level features from its Vision Transformer backbone for refined image-text alignment), and text–timestamp alignment (for precise reasoning over video content and temporal events). These upgrades enable Qwen3-VL to interpret complex scenes, follow dynamic video sequences, read and reason about visual layouts.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

Audience

Developers and AI teams wanting to build private, efficient, on-device multimodal search, retrieval, RAG, and semantic indexing systems

Audience

AI researchers and companies needing a tool to build applications that combine language, vision, and video, from intelligent assistants and content-analysis tools to video understanding pipelines

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Company Information

Google
Founded: 1998
United States
blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/

Company Information

Alibaba
Founded: 1999
China
qwen.ai/blog

Alternatives

Alternatives

Aya Vision

Aya Vision

Cohere
Qwen3.5-Plus

Qwen3.5-Plus

Alibaba
Qwen3.5

Qwen3.5

Alibaba
Qwen3.7-Plus

Qwen3.7-Plus

Alibaba
txtai

txtai

NeuML

Categories

Embedding Models Supported

Categories

AI Models Supported
AI Video Models Supported

Integrations

HTML Not Supported
Hermes Agent Not Supported
OpenClaw Not Supported
Oxen.ai Not Supported

Integrations

HTML Supported
Hermes Agent Supported
OpenClaw Supported
Oxen.ai Supported
Claim EmbeddingGemma 2 and update features and information
Claim EmbeddingGemma 2 and update features and information
Claim Qwen3-VL and update features and information
Claim Qwen3-VL and update features and information