Modèle Aktualisiert 2026-04
Vision-Language Model (VLM)
Vision-Language Model
Definition
A Vision-Language Model (VLM) is an AI model capable of simultaneously understanding and reasoning about images and text, unifying visual perception and language understanding.
Siehe auch im Glossar
M
Multimodal
A multimodal model processes and generates multiple data types: text, images, audio and video.
L
LLM (Large Language Model)
An LLM is an AI model trained on billions of texts, capable of understanding and generating human language.
T
Transformer
The Transformer is the neural network architecture powering all modern LLMs, invented by Google in 2017.
D
Deep Learning
Deep Learning is a subset of Machine Learning using multi-layered neural networks to learn complex representations from raw data.
A
Attention Mechanism
The attention mechanism allows a model to weigh the importance of each word relative to all others, capturing global context.
F
Foundation Model
A foundation model is a large AI model pre-trained on massive data, adaptable to multiple tasks.
Tools, die vision-language model verwenden
C
ChatGPT
Der weltweit meistgenutzte KI-Konversationsassistent
4.6/5
C
Claude
Die KI, die Nuancen versteht – von Anthropic
4.7/5
G
Gemini
Googles KI-Assistent mit 1-Million-Token-Kontext
4.5/5
M
Meta AI (Llama)
Metas KI-Assistent, betrieben von Llama – dem führenden Open-Source-LLM
4.3/5
Q
Qwen
Alibabas LLM mit Stärken in Code und Mehrsprachigkeit
4.4/5
Häufig gestellte Fragen
What's the difference between a VLM and a multimodal model?
A VLM is a specific type of multimodal model focused on vision and language. A multimodal model can include other modalities like audio, video or 3D. In practice, VLMs are the most mature and widely deployed category of multimodal models in 2026.
What is the best VLM in 2026?
Google's Gemini and OpenAI's GPT-4o compete for leadership on visual benchmarks. Anthropic's Claude excels at analyzing complex documents and charts. The choice depends on the use case: OCR, scene understanding, visual reasoning, or diagram analysis.