Multimodal Prompting (Images & Vision)
Multimodal prompting means giving the AI more than text, most often images (and sometimes audio or video). You upload a picture and pair it with a clear instruction: analyze, extract, transcribe, or compare.
Learn Multimodal Prompting (Images & Vision) in our free Prompt Engineering course — a beginner-friendly interactive lesson with worked examples, a practice…
Part of the free Prompt Engineering course at LearnCodingFast — hands-on lessons with examples you run in your browser, plus practice exercises and a quick quiz.
The skill is the same as always: be specific. This lesson shows how to combine images with text instructions and covers common use cases and limitations.
An image alone is not a task. Pair it with a clear instruction about what to do. Same picture, two prompts:
In each case you combine the picture with a precise instruction about what to identify, extract, or compare.
Image models are powerful but not perfect. They can misread blurry, low-resolution, or ambiguous pictures and miss small text or fine detail.
📋 Copy-paste image prompt template
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Practice quiz
What is 'multimodal' prompting?
- Prompting with more than just text, such as images, audio, or video
- Using multiple keyboards
- A faster typing mode
- A type of password
Answer: Prompting with more than just text, such as images, audio, or video. Multimodal means combining text with other inputs like images.
When you send an image, you should also…
- Send it with no instructions
- Delete the image first
- Add a clear text instruction about what to do with it
- Only send the file name
Answer: Add a clear text instruction about what to do with it. Pair the image with a specific text instruction so the model knows the task.
Which instruction is most specific for an image task?
- nice picture
- Extract every line item and total from this receipt as a list
- look at this
- do something
Answer: Extract every line item and total from this receipt as a list. A specific task, extract line items and total, beats a vague request.
OCR with an image model means…
- Deleting the image
- Resizing the file
- Drawing a picture
- Reading text out of an image
Answer: Reading text out of an image. OCR is extracting written text from an image.
A good use case for image prompting is…
- Transcribing a handwritten note
- Sorting your email
- Compressing a video only
- Turning off the screen
Answer: Transcribing a handwritten note. Reading or transcribing text in an image is a classic multimodal task.
Combining an image with text instructions lets you…
- Hide the image
- Tell the model exactly what to analyze, extract, or compare
- Avoid all instructions
- Only see the image
Answer: Tell the model exactly what to analyze, extract, or compare. Text guides what the model should do with the image.
Asking the model to 'compare these two charts' is…
- A drawing task
- Impossible
- Only for text
- A valid multimodal task if both images are provided with a clear instruction
Answer: A valid multimodal task if both images are provided with a clear instruction. Comparison across provided images is a common multimodal use.
A limitation to keep in mind with image prompting is…
- Models never make mistakes on images
- It only works at night
- It can misread blurry, low-resolution, or ambiguous images
- It deletes the image
Answer: It can misread blurry, low-resolution, or ambiguous images. Poor image quality or ambiguity can lead to errors, so verify important results.
For analyzing a diagram, the best prompt…
- asks for a poem
- describes specifically what to identify or explain in the diagram
- just says 'diagram'
- sends no text
Answer: describes specifically what to identify or explain in the diagram. Specific instructions about what to identify produce better diagram analysis.
Which is a strong multimodal prompt?
- Here is a screenshot of an error. Identify the error message and suggest a fix.
- img
- ?
- this
Answer: Here is a screenshot of an error. Identify the error message and suggest a fix.. It names the input, the task, and the desired output.