Gemini has no per-page OCR price. The Gemini API bills tokens, and Google counts each document page as 258 input tokens, so 1,000 invoice pages costs about $0.27 on Gemini 2.5 Flash-Lite, about $1.58 on Gemini 2.5 Flash, and about $5.79 on Gemini 3.5 Flash once you include a realistic structured output. That makes Gemini the cheapest reading layer in this market by a wide margin, roughly fifteen times under Mistral OCR and far under AWS Textract. The cost that is not on the price list is everything between a model response and an invoice your bookkeeper can open. This page converts every current Gemini rate into dollars per 1,000 pages, shows the comparison against the per-page OCR APIs, and flags the two line items that surprise people: thinking tokens billed as output, and a free tier whose content Google uses to improve its products.
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Gemini is almost certainly the cheapest way to read an invoice page in 2026. Working out by how much takes a conversion Google does not do for you, and there are four places the real number drifts from the one on the price list.
Every competing OCR API quotes a price per 1,000 pages. Gemini quotes dollars per million tokens, so the two numbers are not comparable until you convert them yourself. The conversion rate is 258 tokens per document page.
Reading 1,000 pages costs three cents on Flash-Lite. Writing 1,000 structured invoice records costs ten to twenty times that. Any Gemini OCR estimate that only counts input tokens will understate your invoice by an order of magnitude.
The 2.5 and 3 series reason before they answer, and that reasoning is charged as output. A table-heavy invoice with a generous thinking budget can quietly double the cost of a page compared to the arithmetic you did in the spreadsheet.
Google marks free tier content as used to improve its products and paid tier content as not used. For invoices carrying vendor bank details and client names, that makes the free tier the wrong tool regardless of how attractive the price is.
Every current Gemini model rate, converted into the per 1,000 pages figure the rest of the OCR market quotes, with the assumptions written down so you can change them.
258 input tokens per document page, straight from Google’s document processing documentation, applied across every current Gemini model so you can read a per 1,000 page figure instead of doing the arithmetic.
Flash-Lite, Flash, Pro and the preview models, with input and output rates as published in July 2026 and the long prompt surcharges called out where they apply.
The same 1,000 pages priced across Gemini, Mistral OCR, AWS Textract AnalyzeExpense, Azure Document Intelligence and a flat rate invoice tool, including where Gemini genuinely wins.
Thinking tokens billed as output, the free tier data clause, the 50 MB and 1,000 page ceilings, and the page resolution rules that decide whether a scan is worth uploading at full quality.
The math assumes a real invoice record with header fields and line items rather than a plain transcription, because that is what an AP team actually needs out the other end.
Upload invoices at the top of this page and get structured Excel, CSV, JSON or QBO back on a flat monthly plan, with no token meter to watch and no schema to maintain.
A repeatable way to turn the Google token rates into a monthly invoice budget you can defend in a planning meeting.
Gemini bills per page, so a 4 page invoice costs four times a 1 page invoice. Pull the last full month of AP volume and count pages. Most small US finance teams land between 500 and 3,000 pages a month.
Tip: Digital PDFs are cheaper than scans, because embedded text is not charged as tokens.
You need the input and output price per million tokens for the exact model you will call. Start with Gemini 2.5 Flash-Lite unless your invoices are messy scans, in which case try 3.1 Flash-Lite.
Tip: Preview models can change price or be withdrawn. Do not build a budget on one.
Input tokens are pages multiplied by 258. Output tokens are pages multiplied by however long your invoice JSON is, which is around 600 tokens for a typical header plus ten line items.
Tip: Run twenty real invoices first and measure the actual output length instead of guessing.
Schema design, prompt tuning, validation, retries, storage, a review screen and an export. Price that in engineering days, compare it to a flat monthly plan, and pick the cheaper total.
Tip: A single developer week at US rates covers several years of a flat rate invoice tool.
A model endpoint and a finished invoice product are priced differently because they are different things. Here is the honest split.
Above a hundred thousand pages a month the token cost rounds to nothing and the pipeline you build pays for itself. This is where Gemini is unbeatable on price.
The free tier plus 258 tokens a page makes it nearly costless to test whether a model can read your worst vendor layout before you commit to anything.
If you have prompts, evals, retries and observability in production, adding invoices is incremental work rather than a new project.
If nobody on the team writes Python, the per-page rate is not the constraint. A flat plan that exports to Excel and QBO costs less in total than the build.
Google does not publish a per-page OCR rate. The Gemini API bills tokens, and document pages enter as image tokens. These are the current published rates on the paid Standard tier, taken from Google’s developer pricing page in July 2026. Output prices include thinking tokens.
| Model | Input per 1M tokens | Output per 1M tokens | Free tier |
|---|---|---|---|
| Gemini 2.5 Flash-Lite | $0.10 | $0.40 | Yes |
| Gemini 3.1 Flash-Lite | $0.25 | $1.50 | Yes |
| Gemini 2.5 Flash | $0.30 | $2.50 | Yes |
| Gemini 3.5 Flash-Lite | $0.30 | $2.50 | Yes |
| Gemini 3 Flash Preview | $0.50 | $3.00 | No |
| Gemini 2.5 Pro (prompts up to 200k) | $1.25 | $10.00 | No |
| Gemini 3.8 Flash | $1.50 | $7.50 | Yes |
| Gemini 3.7 Flash | $1.50 | $7.50 | Yes |
| Gemini 3.6 Flash | $1.50 | $7.50 | Yes |
| Gemini 3.5 Flash | $1.50 | $9.00 | Yes |
| Gemini 3.1 Pro Preview (prompts up to 200k) | $2.00 | $12.00 | No |
Two rates carry a surcharge on long prompts. Gemini 2.5 Pro moves to $2.50 input and $15.00 output above 200,000 tokens, and Gemini 3.1 Pro Preview moves to $4.00 input and $18.00 output. For invoice work you almost never cross that line, because a single invoice page is 258 tokens.
Google states that each document page is equivalent to 258 tokens, and that tokens from text natively embedded in a PDF are not charged. So 1,000 invoice pages is 258,000 input tokens. Output is the part you control: a plain text transcription is short, while a structured invoice record with header fields and line items is longer. The table below assumes 600 output tokens per page, which is a realistic figure for an invoice JSON record with a dozen header fields and ten line items. Change that assumption and the output column scales linearly.
| Model | Input cost per 1,000 pages | Output cost per 1,000 pages | Total per 1,000 pages |
|---|---|---|---|
| Gemini 2.5 Flash-Lite | $0.03 | $0.24 | $0.27 |
| Gemini 3.1 Flash-Lite | $0.06 | $0.90 | $0.96 |
| Gemini 2.5 Flash | $0.08 | $1.50 | $1.58 |
| Gemini 3.5 Flash-Lite | $0.08 | $1.50 | $1.58 |
| Gemini 3 Flash Preview | $0.13 | $1.80 | $1.93 |
| Gemini 3.8 Flash | $0.39 | $4.50 | $4.89 |
| Gemini 3.7 Flash | $0.39 | $4.50 | $4.89 |
| Gemini 3.6 Flash | $0.39 | $4.50 | $4.89 |
| Gemini 3.5 Flash | $0.39 | $5.40 | $5.79 |
| Gemini 2.5 Pro | $0.32 | $6.00 | $6.32 |
| Gemini 3.1 Pro Preview | $0.52 | $7.20 | $7.72 |
The headline is that the reading step is close to free. On Gemini 2.5 Flash-Lite, the input cost of putting 1,000 invoice pages in front of the model is about three cents. Even on the most expensive Pro preview model, a thousand pages of raw input is around fifty cents. Output tokens, not page tokens, are what your Gemini OCR bill is actually made of.
One caveat that catches people out on their first invoice: the 2.5 and 3 series are thinking models, and Google bills thinking tokens at the output rate. If you leave a high thinking budget on while parsing a table-heavy invoice, the model can spend several hundred reasoning tokens before it writes a single field, and your real output volume lands well above the 600 assumed here. Cap the thinking budget for extraction work and the numbers above hold.
Every other name in this market bills a flat rate per page, so comparing them takes one more step. Here is the same 1,000 pages priced across the options, with the Gemini figure using 2.5 Flash-Lite at the assumption above.
| Option | Cost per 1,000 pages | Billing model | Returns invoice fields? |
|---|---|---|---|
| Gemini 2.5 Flash-Lite | about $0.27 | Tokens | Only if you write the schema and prompt |
| Gemini 3.5 Flash | about $5.79 | Tokens | Only if you write the schema and prompt |
| Mistral OCR 4 | $4.00 ($2.00 on Batch) | Per page | No, returns markdown |
| Mistral Document AI | $5.00 | Per page | Yes, via Annotations |
| AWS Textract AnalyzeExpense | $10.00 | Per page | Yes |
| Azure Document Intelligence, prebuilt invoice | $10.00 | Per page | Yes, with line items |
| InvoiceExtractor Plus | about $14.90 equivalent | Flat $149 a month | Yes, plus review, export and storage |
Read that table honestly and it says something uncomfortable for everyone selling per-page OCR: on raw model cost, Gemini undercuts the dedicated OCR APIs by an order of magnitude. It also says something the price column hides. The first three rows are a model endpoint. The last four are a product. What sits between them is the schema design, the prompt engineering, the retry and validation logic, the confidence handling, the storage, the review screen for the fields the model got wrong, and the export your bookkeeper actually opens. None of that is in the $0.27.
Gemini Flash and Flash-Lite models have a free tier, and that is why so many people search for free Gemini OCR. For a personal project it is genuinely free. For invoice work at a US business it usually is not usable, for one reason that has nothing to do with rate limits: Google’s own pricing page marks the free tier as content used to improve our products, and the paid tier as content not used to improve our products. Client invoices carry vendor names, bank details, addresses and payment terms. If you handle other people’s financial documents, the paid tier is the only defensible choice, and at three cents per thousand pages of input it is not the part of the budget worth optimizing.
The other free tier constraint is throughput. Free tier limits are set per project and Google publishes them in AI Studio rather than in the docs, and they are explicitly not guaranteed. Paid usage tiers move in steps: Tier 1 starts once billing is active with a $250 spend cap, Tier 2 opens at $100 spent plus three days, and Tier 3 at $1,000 spent plus thirty days. A month-end AP run that tries to push several thousand invoices through a free tier key will hit a wall.
On current independent testing, yes on accuracy and clearly yes on price. OCR Arena runs blind community voting between OCR models on real documents, and its published record puts Gemini 3 Flash at ELO 1821 and rank #1 against Mistral OCR v3 at 1576 and rank #9, with Gemini taking 20 of 23 head to head matchups. On cost, 1,000 invoice pages runs about $0.27 on Gemini 2.5 Flash-Lite against a flat $4 per 1,000 for Mistral OCR 4.
Mistral still wins several rows that often decide a purchase. It returns paragraph level bounding boxes and per block confidence scores, which Gemini does not document at all, and those matter the moment a human has to approve an extraction against the original page. Its flat per page rate is forecastable in a way a token bill is not. And it can be self hosted as a single container, while Gemini has no on premise option, so if your controls do not allow vendor documents to leave your network then Gemini is not a candidate at any price.
One honest caveat on the benchmark: it measures Mistral OCR v3, not the newer Mistral OCR 4 released in June 2026, and community voting rewards clean transcription rather than whether the fourth row of a continuation table survived. For accounts payable that second thing is what actually costs money. The full side by side, including a per model cost table, is on our Gemini OCR vs Mistral OCR comparison.
If you have engineers, a queue, somewhere to put the data, and volume in the hundreds of thousands of pages, Gemini is the cheapest reading layer available and the build is worth doing. The token cost genuinely rounds to nothing at that scale, and you keep full control of the schema.
If you are a controller, a bookkeeper, or a three-person finance team, the calculation inverts. A developer week at US rates costs more than five years of our Plus plan. You are not really choosing between $0.27 and $14.90 per thousand pages; you are choosing between a project and a login. Teams that already meter a lot of API spend across their stack tend to find that the invoice line is trivial next to everything else, which is its own argument for not building it: the money is in engineering hours, not tokens, and keeping a clear view of cloud and SaaS spend usually shows the same pattern across the rest of the stack.
Our own pricing is flat on purpose. Starter is $49 a month for 2,500 Base AI pages, which is about $19.60 per thousand. Plus is $149 a month for 10,000 Base AI pages, about $14.90 per thousand. Nobody watches a token meter, nobody writes a schema, and the output lands in Excel, CSV, JSON or QBO. That is a worse per-page rate than Gemini and a better total cost for most finance teams, and both of those statements are true at the same time.
Gemini 3.8 Flash, Gemini 3.7 Flash and Gemini 3.6 Flash all carry the same promotional rate on Google's pricing page: $0.75 per million input tokens and $3.75 per million output tokens through 31 December 2026, rising to $1.50 and $7.50 after that date. The table above uses the post-promotional rates, because those are the numbers a budget written today should survive on. If you are pricing a project that ships this year, the real cost is half.
| Model | Per 1,000 pages until 31 Dec 2026 | Per 1,000 pages from 1 Jan 2027 | Increase |
|---|---|---|---|
| Gemini 3.8 Flash | $2.44 | $4.89 | 2x |
| Gemini 3.7 Flash | $2.44 | $4.89 | 2x |
| Gemini 3.6 Flash | $2.44 | $4.89 | 2x |
Plan for the step-up, not the promotion. A 20,000 page per month AP workload on Gemini 3.7 Flash costs about $49 a month today and about $98 a month from 1 January 2027, for identical output. Promotional model pricing is normal in this market and it always ends. If the business case only works at the promotional rate, it does not work.
Google's document processing documentation states that each document page is equivalent to 258 tokens, and that on Gemini 3 models the tokens from text natively embedded in a PDF are not charged, while pages processed as images are counted under the image modality. In practice that means a born-digital vendor invoice with a real text layer bills less than a scanned one, and the difference is not something the API tells you about after the fact. If most of your AP volume arrives as emailed digital PDFs rather than scans, your effective Gemini rate is lower than any table can show. Batch requests take a further 50% off across the models that support them, and a single request accepts up to 1,000 pages or 50 MB.
Rates and limits on this page re-read from Google's official Gemini API pricing and document processing documentation on 26 August 2026.
Gemini has no per-page OCR price. It bills tokens, and each document page counts as 258 input tokens. On Gemini 2.5 Flash-Lite at $0.10 per million input and $0.40 per million output tokens, 1,000 invoice pages costs roughly $0.27 all in. On Gemini 3.5 Flash it is roughly $5.79 for the same 1,000 pages.
Reading a page costs 258 input tokens, which is $0.000026 on Gemini 2.5 Flash-Lite and $0.00039 on Gemini 3.5 Flash. Your total per page depends on how much the model writes back. A structured invoice record of about 600 output tokens brings 2.5 Flash-Lite to roughly $0.00027 a page and 3.5 Flash to about $0.0058.
Gemini Flash and Flash-Lite models have a free tier, so light OCR use costs nothing. Google states that free tier content is used to improve its products, while paid tier content is not. For client invoices or any regulated financial document, use the paid tier. At about three cents per thousand pages of input, the saving is not worth the exposure.
Yes. Gemini reads PDFs natively as images, up to 1,000 pages per document and 50 MB per file. Text already embedded in the PDF is extracted and not charged as tokens, so a digital invoice costs less than a scan. PDF is the only document format that gets true vision processing; TXT, HTML and XML are read as plain text.
Gemini 2.5 Flash-Lite, at $0.10 per million input tokens and $0.40 per million output tokens. It works out around $0.27 per 1,000 invoice pages. Gemini 3.1 Flash-Lite is the next step up at about $0.96 per 1,000 pages and generally handles messier layouts better, which is usually worth the extra seventy cents.
On raw rates, yes, by a wide margin. Mistral OCR 4 is a flat $4 per 1,000 pages, or $2 through the Batch API, while Gemini 2.5 Flash-Lite lands near $0.27 for the same volume. The difference is what you get back: Mistral returns clean markdown from a purpose-built OCR model, and Gemini returns whatever your prompt and schema ask for.
Almost always thinking tokens. Gemini 2.5 and 3 series models are thinking models, and Google bills thinking tokens at the output rate. On a dense invoice table the model can spend hundreds of reasoning tokens before writing a field. Cap the thinking budget for extraction work and your costs return to the expected range.
Only if you build that. Gemini returns text generated from your prompt, so getting a vendor name, invoice number, due date, tax total and line items back as reliable JSON means writing a response schema, a prompt, validation rules and retry logic, then maintaining all of it as vendor layouts change. Purpose-built invoice tools ship that layer already built.
Google bills $0.10 per document in 10-page blocks where Azure and AWS bill $10.00 per 1,000 pages. Costed at eight document lengths.
Alibaba's qwen-vl-ocr rate card, and the region trap that costs US buyers 150%.
Open weights, no licence fee: what DeepSeek OCR really costs per 1,000 pages.
Agentic Document Extraction credit math: 1 cent a credit, from 0.5 credits a page.
Credits, not pages: $1.25 per 1,000 credits and 1 to 45 credits a page.
Claude bills tokens with no OCR product: 2,714 visual tokens a page, from $6.77 per 1,000.
The other token-metered option: full GPT-4o and GPT-5 per-page math, from $0.47 per 1,000.
Head to head: $0.27 per 1,000 pages on tokens versus $4 flat, plus independent accuracy scores.
Mistral OCR is $4 per 1,000 pages flat. See how the two billing models compare.
The other Google option: the prebuilt Invoice Parser, priced per page rather than per token.
AWS Textract AnalyzeExpense at $10 per 1,000 pages, with the per-page math shown.
Azure prebuilt invoice pricing and what its free tier actually reads.
Prefer an API that already returns invoice fields? Skip the schema build entirely.
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