Multimodal model A model that can take in pictures, sound or video as well as words.
Short answer. A multimodal model is an AI model that works with more than one kind of data, such as text together with images, audio or video. Most open models called multimodal accept images and text and answer in text: Gemma 3 takes images normalised to 896 by 896 pixels, each encoded as 256 tokens, within a 128K-token context. Some also listen and speak: Qwen2.5-Omni perceives text, images, audio and video and can reply with text and natural speech. Images use up the context window like words do, so ten page images cost 2,560 tokens in Gemma 3, and what the model reads from a picture still needs checking.
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How it works
A language model reads tokens. To handle another kind of data, a separate encoder turns it into a sequence of vectors, and a small connecting layer, often called a projector, maps them into the language model’s own space so it can treat them like tokens. The design in the LLaVA paper connects a vision encoder to a language model in this way, and Hugging Face describes the usual vision-language layout as an image encoder, a projector and a text decoder.
Most such models output text only. Some, such as Qwen2.5-Omni, add a part that produces speech. Generating images is a different family of models, called diffusion models, and is usually done by a separate system.
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What some open models accept, as of October 2026
Model
Input
Output
Worth knowing
Gemma 3 (4B, 12B, 27B)
Text and images
Text
128K-token context; images normalised to 896 by 896 pixels and encoded as 256 tokens each; the 1B size is text only
Qwen2.5-VL
Text, images and video
Text
Native dynamic resolution; the report highlights document parsing and long-video understanding
Qwen2.5-Omni
Text, images, audio and video
Text and speech
Streaming responses; separate parts for thinking and talking
Gemma 4
Text, audio and image
See its model card
Long context of up to 256K tokens, under Apache 2.0, per Google’s licence page
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What non-text input costs
Every image, clip or sound becomes tokens in the context window and entries in the KV cache. With Gemma 3, one image is 256 tokens regardless of content, so ten scanned pages are 2,560 tokens, less than the roughly 6,500 tokens of ten text pages of 500 words each. But a fixed 896 by 896 canvas means a full page is scaled down, and small print can be lost. Models that handle the image at its own resolution, as Qwen2.5-VL does, use more tokens for bigger images.
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Cautions
Misreading: a model can read a digit wrongly and say so with confidence. Check amounts and dates against the image.
Hidden instructions: text inside an image is still text the model may obey. Treat images from outside the office as untrusted input.
Personal data: photos and scans often contain faces, signatures and ID numbers. Keep them on the machine and out of logs you do not control.
Files: running a vision model in llama.cpp can need a second file, the projector, which its naming rules mark with the prefix mmproj. Check the licence of both.
Memory: the vision part adds parameters, and each image adds to the cache.
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Where ANVE stands
In the development build, image generation runs on the box’s own GPU through ComfyUI, vision models read scanned documents, photos, diagrams and video frames, and a bills feature reads GST bills. No sealed unit exists yet.
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Questions people ask
Is a multimodal model the same as a vision-language model?
A vision-language model is one kind of multimodal model, limited to images or video together with text. Multimodal also covers audio and other inputs.
Can multimodal models create images?
Most of the models above output text only, and Qwen2.5-Omni can also speak. Images are usually generated by a separate diffusion model, which a system can call alongside the language model.
Do multimodal models use more memory?
Yes. They carry an extra encoder, and every image, clip or sound adds tokens to the context and the KV cache.
Can they read Hindi or other scripts in a picture?
Sometimes. Support varies by model and by script, and handwriting is harder than print. Test with your own samples before relying on it.
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What is not real yet
No sealed ANVE unit exists; every image of the appliance on this site is a labelled render. The software runs today on a development machine. No customers yet, no certifications, no delivery date, and the final price is not announced.
Reservations are ₹999 in India or US$12 elsewhere, refundable in full until you confirm an order in writing (terms). Offices that cannot use cloud AI can apply to be one of ten design partners.
