Uploaded October 2025 | Updated September 2026, 2 hours ago
Meet DeepSeek-OCR, the new kid rewriting how we handle long-context vision. Instead of forcing LLMs to digest endless text, it compresses text into vision tokens—turning documents into a compact optical language. The result? 97% accuracy at a 10× compression ratio and 60% even at 20×. That’s wild.
This model runs a Mixture-of-Experts decoder that beats 7B+ vision models with just 570M active params, thanks to smart token efficiency—not brute force. It can parse everything from tables and formulas to multilingual documents, Markdown, even chemical notation.
It’s a glimpse of where multimodal systems are heading: token efficiency model size. The age of “context without compromise” might just be starting.
I’m Louis-François, PhD dropout, now CTO & co-founder at Towards AI. Follow me for tomorrow’s no-BS AI roundup 🚀
#DeepSeekOCR #AIresearch #LLM #short
Meet DeepSeek-OCR, the new kid rewriting how we handle long-context vision. Instead of forcing LLMs to digest endless text, it compresses text into vision tokens—turning documents into a compact optical language. The result? 97% accuracy at a 10× compression ratio and 60% even at 20×. That’s wild.
This model runs a Mixture-of-Experts decoder that beats 7B+ vision models with just 570M active params, thanks to smart token efficiency—not brute force. It can parse everything from tables and formulas to multilingual documents, Markdown, even chemical notation.
It’s a glimpse of where multimodal systems are heading: token efficiency model size. The age of “context without compromise” might just be starting.
I’m Louis-François, PhD dropout, now CTO & co-founder at Towards AI. Follow me for tomorrow’s no-BS AI roundup 🚀
#DeepSeekOCR #AIresearch #LLM #short
