Every AI model has some restrictions as to which file types you can upload and work with. Today, I’m going to make this easy for you with a clear breakdown of every file type you can work with.
Geekflare Chat lets you upload files directly into a conversation and ask questions about them. You will find all these file types supported:
| File Type | Formats |
|---|---|
| Documents | PDF, DOCX, TXT |
| Images | PNG, JPG, JPEG, WEBP |
There is a per-file size limit for every upload. But before you get down to uploading anything, you need to know two things:
- Chatting with file uploads is only available on Pro ($9/month) and above plans. The Free plan doesn’t include it.
- Every message you send against an uploaded file in the Knowledge Base adds 5 credits to the model’s base cost. So, a Lite model query against your file costs 6 credits, while an Advanced model query costs 20 credits.
You can check out the credits explainer for the full breakdown.
Uploading your 1st PDF
This process hardly takes 10 seconds.
Step 1: Fire up a new conversation in Geekflare Chat and pick your preferred model from the dropdown. For this test, we are going to go with GPT 5.4, as it’s pretty good at handling documents.
Step 2: Click the file upload button (the attachment icon next to the chat input), select your PDF file, and wait for the upload confirmation. Once the file is uploaded, you will see a file indicator appear in the conversation.
Step 3: Ask the question that you want answered. The model will now use your document as context and will answer based on its contents.
One thing people miss on their first upload: the model reads the document once when you attach it, and every follow-up question in that same conversation can reference it. You don’t need to re-upload or re-attach for each new question. The file remains in context throughout the thread.
Asking the Right Questions: Bad Prompt vs. Good Prompt
You are only done with the easy part of uploading the PDF. The next part about prompting is where most people leave value on the table.
Let me tell you what a bad prompt looks like:
Summarize this document.
You will get a summary, but that’s all. It will be vague and cover everything at the surface level. The model isn’t going to return any specific details you actually care about. That’s because the model has no idea about what matters to you, so it’s only going to give you generic outputs.
Instead, try a prompt like this:
Summarize this report in three sections: (1) the three most important findings, (2) any specific statistics or data points cited, and (3) the authors' recommendations. Keep each section under 100 words.
This is where you add structure and constraints for the output. You are telling the model exactly what you are looking for, how to organize that information, and how long each section should be. This is how you go from vague outputs to something that you can actually paste in your team’s Slack channel.
I know it’s not easy to write such prompts all the time, so let me give you a few more ideas:
- For contracts and legal documents: List every obligation, deadline, and penalty clause in this agreement. Include the section number for each.
- For financial filings: Extract all revenue figures, growth percentages, and forward-looking projections. Format as a table with columns for Metric, Value, and Page Number.
- For research papers: What methodology did the authors use? What were the limitations they acknowledged? Do any of their conclusions contradict their own data?
If you carefully read through every prompt, you’ll see that they ask for specific outputs and specify exactly how they want the answers formatted.
Uploading an Image and Asking for Analysis
You can upload an image the same way you upload a PDF file. Click the attachment button, select an image of your choice, and you are ready to ask questions.
This feature is extremely useful when you have visuals that need interpretation. Upload a photo of a whiteboard from a meeting and ask the model to transcribe and organize the notes. Upload a dashboard screenshot and ask it to identify which metric is trending down. You can even upload a product photo and ask for a description you can use in a listing.
Let me give you a prompt that works pretty well for image analysis:
Describe what's in this image in detail. Then identify the three most important pieces of information visible and explain why they matter.I want you to keep one thing in mind: image understanding varies by model. Both GPT-5.4 and Claude Sonnet 4.6 are good at image analysis, but they interpret images differently. GPT tends to be more literal and descriptive. Claude tends to infer context and suggest implications. If the first model’s interpretation doesn’t match what you need, switch to another model. Your image stays in the conversation, just like PDFs.
If you want to analyze any PDF with embedded charts, which is a document that mixes text and visuals, then I’ll suggest going for GPT-5.4, as it’s pretty reliable at handling this combination.
Which Model to Pick for Which File Type?
I’ve tried running the same files through different models on Geekflare Chat, so that you know which model to pick for specific tasks.
| Task | Best Pick | Why |
|---|---|---|
| Long PDF summarization | Claude Sonnet 4.6 | Strongest at reading long documents and producing summaries that actually sound written, not generated. |
| Data extraction into tables | GPT-5.4 | Cleanest table formatting. Follows column specs precisely and rarely misses entries. |
| Image description and analysis | GPT-5.4 | Most detailed visual descriptions. Handles mixed-content documents (text + charts) better than alternatives. |
| Quick factual lookups from a doc | Gemini 3.1 Pro | Fastest for “find this number on page X” queries. Less thorough on follow-ups, but fast on retrieval. |
| Cross-referencing multiple files | Claude Sonnet 4.6 | Best at holding multiple documents in context and flagging where they agree or contradict. |
The best thing is that you don’t have to limit yourself to a single model for the whole conversation. You can upload your PDF, have it summarized by Claude, switch to GPT for structured extraction, and then ask Gemini to run the factual check. And even though you are switching models mid-conversation, your file and chats carry over. You won’t lose context in between these switches.
For the full breakdown on how different models perform across non-document tasks, the side-by-side comparison guide covers writing, coding, research, and reasoning.
Your Files Stay Private
Every model request in Geekflare Chat goes through commercial API endpoints from OpenAI, Anthropic, and Google. These aren’t the same pipelines as the free consumer versions of ChatGPT or Gemini. The API endpoints operate under data-use agreements that explicitly prohibit the use of your inputs. So, it’s clear that Geekflare Chat never uses your uploaded files or data to train its underlying models.
Your PDFs, Word docs, and images aren’t feeding a training dataset. They’re processed for your query, the response is generated, and the data stays in your workspace. On team plans, workspace isolation means your files are visible only to members of that specific workspace. Nobody outside your team sees them.
If you’re uploading client contracts, financial filings, internal strategy documents, or anything confidential, this distinction matters. Most free PDF-chat tools don’t offer this guarantee. Some explicitly state in their terms that uploaded files may be used for model improvement. Read the fine print before you upload anything sensitive elsewhere.
This is why you can’t rely on free PDF-chat tools right now. Instead, sign up for Geekflare Chat, and you won’t have to worry about privacy or safety anymore.
