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This peanut-sized chinese model just dethroned Gemini at reading documents. It’s called glm-ocr. it’s a tiny 0.9b parameter vision-language model that is about to replace every expensive ocr api you use. → Handles text, tables, formulas, handwriting → Scored 94.62 on OmniDocBench V1.5 → 8 languages → vLLM, SGLang,...

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Alvaro Cintas

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37,477 görüntüleme • 2 ay önce •via X (Twitter)

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Everyone is sleeping on this new OCR model! Datalab's Chandra topped independent benchmarks and beat the previous best dots-ocr. - Supports 40+ languages - Extracts complex texts, tables, formulas easily I tested on Ramanujan's handwritten letter from 1913. 100% open-source.
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Everyone is sleeping on this new OCR model! Datalab's Chandra topped independent benchmarks and beat the previous best dots-ocr. - Supports 40+ languages - Extracts complex texts, tables, formulas easily I tested on Ramanujan's handwritten letter from 1913. 100% open-source.

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Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!
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Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!

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ByteDance just dropped an OCR model that reads documents just like humans. This 0.3B model analyzes page layout first, then parses elements in parallel. 100% open-source.
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ByteDance just dropped an OCR model that reads documents just like humans. This 0.3B model analyzes page layout first, then parses elements in parallel. 100% open-source.

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Announcing llama-ocr – a free + open source OCR tool! It takes documents (images for now) & outputs markdown, and does really well for complex receipts, PDFs with tables/charts, ect... Powered by Llama 3.2 vision on Together AI & available on npm today!
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Announcing llama-ocr – a free + open source OCR tool! It takes documents (images for now) & outputs markdown, and does really well for complex receipts, PDFs with tables/charts, ect... Powered by Llama 3.2 vision on Together AI & available on npm today!

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smart parking demo - RF-DETR - license plate detection - OC-SORT - multi-object tracking - GLM-OCR - reading license plates on Monday I showed you trackers, yesterday GLM-OCR, today I'm putting everything together
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smart parking demo - RF-DETR - license plate detection - OC-SORT - multi-object tracking - GLM-OCR - reading license plates on Monday I showed you trackers, yesterday GLM-OCR, today I'm putting everything together

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Ok... this is insane! Alibaba just dropped Wan2.2-S2V, a 14B parameter speech-to-video model. Turn audio into film-grade clips with lifelike motion and environment control. And it’s fully open-source. Examples below: (sound on)
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Ok... this is insane! Alibaba just dropped Wan2.2-S2V, a 14B parameter speech-to-video model. Turn audio into film-grade clips with lifelike motion and environment control. And it’s fully open-source. Examples below: (sound on)

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GPT-4o level multimodal LLM running on your phone. MiniCPM-V 4.5 outperforms GPT-4o, Gemini-2.0 Pro, and Qwen2.5-VL 72B on vision and language AI tasks. It can even understand videos and perform OCR in 30+ languages. And it's 100% Opensource.
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GPT-4o level multimodal LLM running on your phone. MiniCPM-V 4.5 outperforms GPT-4o, Gemini-2.0 Pro, and Qwen2.5-VL 72B on vision and language AI tasks. It can even understand videos and perform OCR in 30+ languages. And it's 100% Opensource.

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NVIDIA Nemotron 3 Nano Omni, a new multimodal reasoning model, is now live on Jetson AI Lab and unifies vision, audio, and language into a single reasoning loop. 🙌 Power your NemoClaws by running this model with Ollama, vLLM and other inference frameworks on NVIDIA Jetson hardware. Try it ➡️

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Happy Friday! We just put DeepSeek-V4-Pro up on It’s the world’s largest open source model at 1.6T parameters, and you can run it for free running on NVIDIA Blackwell GPUs. Try the NVIDIA NIM API →

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Good to know: MinMax-M2 is one of the best model at UI design 👀 (it’s open source!)

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Google just open-sourced LangExtract Python library! It uses LLMs to extract entities, attributes, and relations—with exact source grounding—from unstructured documents. Flexible LLM support (Gemini, OpenAI, Ollama) 100% open-source.

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Gemini 3 Flash is now available in MagicPath ⚡ From our earlier testing, it’s surprisingly strong at visual design for its size, and it’s fast! My recommendation: use it as your first-pass model to explore ideas, then switch to a bigger model for editing + refinements.
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Gemini 3 Flash is now available in MagicPath ⚡ From our earlier testing, it’s surprisingly strong at visual design for its size, and it’s fast! My recommendation: use it as your first-pass model to explore ideas, then switch to a bigger model for editing + refinements.

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From writing emails to building entire applications... The AI evolution is mind-blowing! GLM-4.6 just dropped and it's changing everything. It’s fast. It’s smart. And it’s packed with features no other model has right now. Here’s why it’s blowing people’s minds 👇

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Moondream doesn’t just OCR, it understands. Full JSON receipts, instant Q&A. Open, tiny, blazingly fast.
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We are building “Open Source Nano Banana for Video” - here is open source demo v0.1 We are open sourcing Lucy Edit, the first foundation model for text-guided video editing! Get the model on Hugging Face 🤗, API on @FAL, and nodes on ComfyUI 🧵

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