Ready
0 chars · 0 words
checks per rolling 24 hours
5
characters per section
12,000
affiliation with Turnitin
None

The output

What the Llama Turnitin checker gives you

Written findings on one section of a draft: where sentences run to the same length, where paragraph openings repeat, where transitions are interchangeable, where an assertion is standing on its own without an example. No number comes back, because this is not Turnitin and has no connection to it, so there is no score here to be had.

Plan around that from the start. The output is a list of places to look, which is usable in an editing session. It is not a clearance, it is not a prediction, and treating it as either will lead you to the wrong decision at the worst possible moment.

Sequencing

Where a draft check fits before submission

In the editing pass, not the panic hour. Running it the night before a deadline produces findings you cannot act on, which converts useful information into anxiety.

The productive slot is after the argument is settled and while you still have a day or two to rewrite paragraphs.

Too early
Outline or partial draft. Findings describe gaps you already intend to fill.
Right time
Complete section, structure fixed, with time left to rewrite. Every finding maps to a paragraph you can open.
Too late
An hour before submission. Nothing you learn can be acted on, and a bad reading at that point helps nobody.

Workflow

How to run the Llama Turnitin checker in three steps

The section is posted to our AI server, read there and returned in the same response. Nothing is submitted to any academic repository.

Step 1
Paste one section of 1 to 12,000 characters. Longer input is refused before the check is spent.
Step 2
Name the section and its job in up to 300 characters, for example: this is a discussion chapter and should read as an argument, not a summary.
Step 3
Edit the specific paragraphs the findings name, and keep the earlier version rather than overwriting it.

Habit worth building

Keeping evidence of process while you draft

Detectors read the finished text and nothing else. That is precisely why the finished text is useless for defending yourself: it cannot show how it came to exist. The defence is process, and process only exists if you kept it.

This costs almost nothing during writing and is unrecoverable afterwards. University guidance tells staff to treat a detection result as the start of a conversation and to stay open to it being wrong, which is a conversation you can only win with material.

Version history
Write somewhere that keeps timestamps. Dated versions are the strongest single piece of evidence.
The ugly draft
Keep the version with the wrong structure and the abandoned paragraph. Models do not produce those.
Reading notes
Quotes, page numbers and your own marginal reactions, dated as you read.
A record of tool use
If you used a model for an outline or a summary, note where. Declared use is a different conversation from discovered use.

Triage

Which sections are worth spending a check on

Five checks per rolling 24 hours does not cover a thesis, so pick deliberately. The sections where generic writing is a real problem are the ones carrying an argument: introduction, discussion, conclusion.

Methods and literature review will come back looking uniform and repetitive because that is what those genres require. A check there mostly tells you that the conventions of the field are the conventions of the field, which is a run you will not get back.

Scope

What the Llama Turnitin checker will not do

It will not produce a Turnitin score, a probability, a risk band or highlighted sentences, and it will not tell you whether you will be flagged. No tool outside your institution can, and the ones that offer it are selling a number they made up.

It will not check plagiarism, rewrite your draft, humanize anything or promise that any system will find your work clean. It analyses and reports, and nothing edited comes back.

Privacy

A server route, and what does not happen to your file

The text goes to our AI server so a language model can read it. The watermark and hidden character tools here run locally and transmit nothing; this one does transmit, and saying so plainly is part of using it sensibly.

What does not happen is worth stating too, because it is the fear people arrive with. Your section is not submitted to any academic database, not stored as a paper, not indexed and not made available for a future similarity check to match against. No account is created and the allowance is tracked against a hashed identifier.

In practice

Who runs the Llama Turnitin checker, and when

Students in the final editing week who want their own writing read back to them. Writers who drafted a section with a model, rewrote it properly, and want to know how much of the original shape is still showing. People who have been through a misconduct conversation once and are now over-correcting on every formal sentence.

The honest value is editorial rather than protective. It points at the paragraphs where the writing stopped saying anything specific, and those are worth rewriting on their own merits, whatever any detector would have made of them.

FAQ

Everything answered. Running the Llama Turnitin checker

Is this connected to Turnitin?

No. No affiliation, no access to its system, and no way to run its check from this page.

Can it predict my Turnitin score?

No. That number comes from a system we have no access to, and guessing it would be dishonest.

What do I get instead?

Written findings on where the section has gone generic: repetition, uniform sentence length, missing specifics.

How do I run a check?

Paste one section of up to 12,000 characters, name what the section is for, and run it.

Is it free?

Yes. Five checks per rolling 24 hours, with no account, card or email.

Will my draft be stored or submitted anywhere?

No. It is not submitted to any academic database and not kept as a paper.

Is the text sent to a server?

Yes, to our AI server, because reading a passage needs a language model.

Which sections should I check?

Introduction, discussion and conclusion. Those carry an argument that can genuinely fail.

Why does my methods chapter look bad?

Methods writing is meant to be uniform. A finding about repetition there is describing the genre.

Can honest work be flagged by a detector?

Yes. Formal tone, technical vocabulary and heavy editing all push writing toward the patterns detectors react to.

What should I keep while drafting?

Dated versions, the messy early draft, reading notes, and a record of any tool you used.

What do I do if I am accused?

Bring process evidence. Institutions are told to use a detection result to start a conversation, not to treat it as proof.

Does it rewrite or humanize my text?

No. It reads and reports, and nothing edited is returned.

Does it check plagiarism?

No similarity search and no source database exist on this route.

Can I check a whole thesis?

No. 12,000 characters per check means section by section.

How many checks do I get a day?

Five per rolling 24 hours, counted against a hashed identifier.

Is there a batch mode or an API?

Neither. One section per check, through the page.

Does it work on a phone?

Yes. A text field and a button in any current browser.

Is this connected to Meta?

No affiliation with Meta or with Llama, and no claim about which model serves the request.

What happens when the checks run out?

The run is refused with the reset time and nothing is sent onward.

Is using this against academic rules?

Getting feedback on your own writing is normally fine, but your institution sets the policy, so read it.

Should I edit purely to avoid a flag?

No. Edit because the paragraph was vague. Writing for a score you cannot see is guesswork.