Instead of feeding model a kilometer-long text, Glyph turns it into an image and processes it through a vision-language model.
🟢 How it works?
A LLM-driven genetic algorithm is used to select the best parameters for the visual representation of the text (font, density, layout), balancing compression and accuracy.
This drastically reduces computational costs while preserving the semantic structure of the text.
At the same time, accuracy hardly drops: on long-context tasks, Glyph performs at the level of modern models like Qwen3-8B.
With extreme compression, a VLM with a 128K context can effectively handle tasks equivalent to 1M+ tokens in traditional LLMs.
In fact, long context becomes a multimodal task rather than purely textual.
HF & Repository
#AI #LLM #Multimodal #Research #DeepLearning
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