Granite Vision 3.3 2B is a compact vision-language model built for one specific job: reading and making sense of visual documents. If your workflow involves pulling data from charts, tables, infographics, or technical diagrams, this model handles the extraction for you without manual copying or transcription. Feed it an image of a financial table and ask for specific row values. Point it at a scientific chart and request a plain-language description of each section. Drop in a screenshot of a dense infographic and ask what the main figures are. The model reads the visual structure, interprets the data, and returns a focused text response to your question. It fits naturally into document-heavy workflows where manual reading is slow and error-prone. Upload a screenshot, type your question, and get the answer in seconds. If the first response isn't right, adjust the temperature or refine your prompt and run it again. No setup required beyond choosing your image.
Granite Vision 3.3 2B is a compact vision-language model built to read and extract structured information from visual documents, solving a problem that standard text tools cannot: making sense of tables, charts, infographics, plots, and diagrams as usable data. Think of a financial analyst pulling quarterly figures from a scanned report, or a researcher transcribing a methodology diagram without retyping a single cell by hand. On Picasso IA, you upload an image and write a plain-language question, and the model returns a focused, readable answer in seconds. At 2 billion parameters, it stays fast without trading away the accuracy that document extraction work demands.
Do I need programming skills or technical knowledge to use this? No, just open Granite Vision 3.3 2B on Picasso IA, adjust the settings you want, and hit generate.
Is it free to try? Yes, you can run Granite Vision 3.3 2B without any upfront cost. Check the pricing section on Picasso IA for details on how generation credits work.
How long does it take to get results? Most requests return within a few seconds. Processing time depends on image complexity and the length of output you have requested, but the 2B parameter size keeps things fast compared to larger vision models.
What kinds of images does it handle best? It performs well on tables, bar charts, pie charts, infographics, technical diagrams, scatter plots, and text-heavy slides. It works with both clean digital images and moderately compressed scans.
What output formats can I get? The model returns plain text by default. You can shape the format through your prompt: ask for a markdown table, a JSON object, a numbered list, or a short paragraph and it will match the structure you describe.
Can I send multiple images in one request? Yes. The model accepts an array of image inputs, so you can feed in several document pages at once and ask questions that span across them in a single generation.
What if the output misses a detail or gets something wrong? Try rephrasing your prompt to be more specific about what you want extracted. Lowering the temperature setting toward 0 typically produces more precise, fact-focused answers when working with structured data.
Everything this model can do for you
Extracts text, data, and context from charts, tables, and infographics in a single request.
Send multiple images at once to process paginated documents or compare visual sources.
Set minimum and maximum token counts to get brief summaries or detailed breakdowns.
Lower the temperature for precise factual extraction, raise it for more descriptive answers.
Set a role or context before each session to keep responses consistent across your workflow.
Fine-tune how the model selects tokens for more varied or more focused outputs.
Define custom stop tokens to end generation exactly where you need it.
