Reading documents models that run on 8 GB
20 models with published weights that fit in 8 GB — a phone, a base iPad, an Air. Counted at four-bit quantisation, weights only, leaving the machine about a third of its memory and a gigabyte for context: room for roughly 7 billion parameters. A mixture of experts is counted in full, because it is held in full even though only a few experts compute.
The memory of a phone, a base iPad or an entry-level laptop. What fits is small: models of a few billion parameters, quick and cheap to run, good at summarising, classifying and simple extraction, and out of their depth on long reasoning. This is also where on-device makes the most sense, because the alternative is a network round trip for something that takes a moment.
Models that read documents — scans, photographs of pages, forms, tables — and return text or structure. The interesting difference between them is not whether they can read a clean page, which they all can, but what they do with a table, a stamp, a handwritten margin or a column that breaks across pages. Several are priced per page rather than per token, which makes them easy to budget and hard to compare with the rest.
- llava-v1.6-mistral-7b-hfLlava Hugging Face7.0B≈4.5 GB at 4-bit
- olmOCR-2-7B-1025Allen Institute for AI (Ai2)7.0B≈4.5 GB at 4-bit1 also selling it hosted
- olmOCR-7B-0725-FP8Allen Institute for AI (Ai2)7.0B≈4.5 GB at 4-bit1 also selling it hosted
- olmOCR-7B-0825Allen Institute for AI (Ai2)7.0B≈4.5 GB at 4-bit1 also selling it hosted
- chandra-ocr-2Datalab5.3B≈3.4 GB at 4-bit
- NuExtract3NuMind4.5B≈3.0 GB at 4-bit
- Unlimited-OCRBaidu3.3B≈2.2 GB at 4-bit
- dots.ocrdots studio3.0B≈2.0 GB at 4-bit
- Isaac 0.2 2B PreviewPerceptron2.0B≈1.3 GB at 4-bit1 also selling it hosted
- LightOnOCR-1B-1025LightOn AI1.2B≈0.8 GB at 4-bit
- HunyuanOCRTencent Hunyuan1.1B≈0.7 GB at 4-bit
- LightOnOCR-2-1BLightOn AI1.0B≈0.7 GB at 4-bit
- Isaac 0.2 1BPerceptron1.0B≈0.7 GB at 4-bit1 also selling it hosted
- PaddleOCR-VL-1.5paddlepaddle1.0B≈0.6 GB at 4-bit
- PaddleOCR-VL-1.6paddlepaddle1.0B≈0.6 GB at 4-bit
- PaddleOCR-VL-0.9Bpaddlepaddle0.9B≈0.6 GB at 4-bit1 also selling it hosted
- OvisOCR2ATH-MaaS0.9B≈0.6 GB at 4-bit
- GOT-OCR2_0StepFun0.7B≈0.5 GB at 4-bit
- GOT-OCR-2.0-hfstepfun-ai0.6B≈0.4 GB at 4-bit
- trocr-base-handwrittenMicrosoft0.3B≈0.2 GB at 4-bit