Neither assistant wins by default: which one writes better eBay listings depends on your stock, so run the same ten items through both and score titles, item specifics and accuracy. On safety, ChatGPT with model training switched off is the lower-risk home for seller data. With DeepSeek, paste only public product facts, never buyer details.
The usual mistake is judging on one flashy title. A single good output proves nothing, and a single bad one proves less. What separates the two tools in practice is how often they invent an item specific you never gave them, how well they pack the 80 characters eBay allows in a title, and where your pasted text ends up afterwards. All three can be tested in about an afternoon.
Why a ten-item test beats reading reviews
Reviews of AI models go stale within weeks, and they test generic tasks such as essays and code. Your listings are narrow: a short keyword-dense title, a list of item specifics (the structured fields such as brand, model, colour and size), and a description that states condition honestly. A model that writes lovely prose can still be poor at this.
Ten items is enough to see patterns without turning the test into a project. Choose them to stress the weak spots rather than to flatter the tools:
- Three easy items with a clear brand and model number.
- Three awkward ones: unbranded, vintage, or sold as a lot.
- Two items with a flaw to disclose (a scratch, a missing cable).
- Two where the title limit hurts, because the product name is already long.
Say the seller is a part-time reseller of kitchen and small-appliance items. The ten might include a stand mixer with its bowl missing, a boxed set of three unbranded steel pans, a vintage enamel jug and a branded coffee grinder with a hairline crack in the lid. Those four alone expose most of the differences you care about.
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A fair comparison needs identical input. For each item, write a few lines of facts in a plain text file, the way you would jot them while holding the item. Do not tidy them into sentences, because messy notes are what you will really paste.
ITEM 4
Brand: (none on base) Lid says "Cafe Pro"
Type: electric burr coffee grinder
Condition: used, works, hairline crack on lid (does not affect use)
Size: 22 cm tall, 250 W
Colour: black/silver
Includes: lid, hopper, cleaning brush. No manual.
Notes: bought 2021, used weekly
Then use one prompt for both tools. Keep the rules in the prompt, so the only variable is the model:
You write eBay listings for a small reseller. Use ONLY the facts I give you.
Never add a brand, model number, size, material or feature I did not state.
If a detail is missing, write "[CHECK: ...]" instead of guessing.
Give me:
1. A title of 80 characters or fewer, most searchable words first.
2. Item specifics as "Field: value" lines for: Brand, Type, Colour, Material, Condition, Features.
3. A description of 90-130 words, plain tone, with every flaw stated.
ITEM:
[paste item notes]
Open a fresh chat for each item, so one item's details cannot leak into the next. Paste the output into a spreadsheet with one row per item per tool. The "Never add a brand" and "[CHECK: ...]" instructions matter: they turn invention into a visible flag you can count.
Score three things, not "which reads nicer"
Use a 0-2 scale on each row, scored by you against the physical item. Three columns are enough.
| Column | 0 points | 1 point | 2 points |
|---|---|---|---|
| Title | Over 80 characters, or key term missing | Fits, but wasted words ("Great", "Look") | Fits, strongest search terms first, nothing wasted |
| Item specifics | Any invented value | All true but fields missing | All true, fields filled or flagged [CHECK] |
| Accuracy of description | Flaw omitted or feature invented | Accurate but vague about the flaw | Every flaw stated plainly, no inventions |
Count the characters yourself or paste the title into a character counter; do not trust the model's own count, because language models routinely miscount. eBay's title limit is 80 characters, so a model that overshoots leaves you cutting words by hand, and the words you keep under time pressure are rarely the ones buyers search for.
Add one tiebreak column: edit minutes. Time yourself getting each output to a state you would publish. A tool that scores a point lower but needs two fewer minutes of fixing per item can be the better choice for a seller listing fifty items a week.
What the first title attempt tends to look like
Here is an illustrative pair of outputs for item 4 above. They are examples of the kind of difference to look for, not recorded results from either product.
Output A (title): Cafe Pro Electric Burr Coffee Grinder Black Silver 250W Used Working
= 78 characters. Brand taken from the lid, as stated. Good.
Output B (title): Premium Cafe Pro Professional Burr Coffee Grinder 250W Barista Quality Black
= 79 characters. "Premium", "Professional" and "Barista Quality" are not in the notes.
Output B reads more persuasively and scores worse. It spends characters on claims you cannot back up, and it drops "Used", which buyers filter on. A buyer who feels misled files a "not as described" complaint, and that costs far more than one lost click. Score B a 1 on title and a 0 on accuracy, then note the pattern: this tool leans promotional when you do not forbid it.
If either tool does that, fix it in the prompt rather than in each output. Add a line: "No marketing adjectives. Use only words a buyer would type into a search box." Re-run the three affected items and see whether the score moves. A tool that ignores the instruction is telling you something.
Item specifics are where invention shows up
Titles get the attention, but item specifics are where models most often fill gaps with plausible fiction. Ask for "Material" on the unbranded steel pans and an assistant that has no data may write "Stainless Steel", which is a reasonable guess and may be wrong (it could be coated aluminium). Ask for "Country of Manufacture" and you will see the problem even more clearly.
Your rule for the test: every value must be traceable to your notes or to something visible in your photos. Mark any value you cannot trace as invented, even if it turns out right, because a guess that happens to be correct is still a process failure. On a ten-item test, count the invented values per tool. Zero is the target, and a tool that produces one or two per batch needs a human check on every listing.
Brand-new, boxed stock is easier: you can read model numbers and specifications off the box and paste them. The risk rises on used and vintage goods, which is exactly where a reseller's margin lives.
Three listing situations that separate the tools
The lot or bundle
Describe three unbranded pans in different sizes and ask for a title. A weaker output lists "Set of 3 Pans" and nothing else. A stronger one separates dimensions ("16, 20, 24 cm") and material if you gave it. Score on whether the title tells a buyer exactly what arrives in the parcel.
The vintage piece with partial knowledge
For the enamel jug you may know only "white, blue rim, chip on base, about 1 litre". Good output uses those words, flags the era as [CHECK] and does not pretend to date it. This is the clearest test of whether the model respects the "never guess" rule.
The title that is already too long
A long product name such as a full printer model plus compatible cartridge codes can eat the whole limit. See which tool drops the least useful words first. The right cut is "Genuine" or "New" filler, never the model number buyers search for.
A quick sum on what the edit time is worth
Suppose you list 40 items a week and tool one needs four minutes of editing per item, tool two needs six. That is 160 versus 240 minutes, an 80-minute weekly difference, or roughly 69 hours a year. If your time is worth $15 an hour, that is about $1,040 a year, which dwarfs any subscription difference. Run the sum with your own volume and your own hourly value. If your tests show a tiny difference in edit time, then price and data handling should decide.
Data-safety rules for sellers, whichever tool you pick
This is the part that matters if you ever do more than list a mixer. A seller account touches buyer names, addresses, order histories, supplier prices and sometimes payment-related messages. None of it needs to go into a general chat assistant to write a listing.
Keep this short rule card by your keyboard:
- Never paste: buyer names, addresses, phone numbers, order or tracking numbers, messages containing any of those, account or payout details, supplier contracts, and cost-of-goods spreadsheets.
- Fine to paste: product facts, condition notes, measurements, public model numbers, and your own listing text.
- Photos: crop out parcel labels, handwriting and background clutter before uploading any image to a chat tool.
- Replies to buyers: paste the question only. Write the greeting and the name yourself.
The two tools differ in how much their makers say about where your text goes. For ChatGPT, OpenAI's help centre says sharing for training is on by default on the Free, Plus and Pro plans, and a setting called Improve the model for everyone turns it off; content in Business and Enterprise workspaces is not used for training by default. I'd turn the setting off and keep business chats clearly separate from personal ones. For DeepSeek, its privacy policy (last updated February 2026) says it collects, processes and stores personal data, including what you type and upload, in its home jurisdiction, which may be a different legal area from yours. It keeps data "for as long as necessary" to provide the service, and it lists model training among the uses of your inputs, with a right to opt out that you have to exercise yourself. Its API terms are silent on retention and processing location. That does not make the tool unusable; it means your paste rules must be stricter. The full picture is in Is DeepSeek Safe to Use With Business Data?.
If you want the model quality without sending text to a third party, DeepSeek publishes open-weight versions under the MIT licence, which can be run on your own machine or a server you control. For a part-time seller that is more setup than the listing time saved is worth, but it is the honest answer when someone says "I'd use it if my data stayed with me".
Three settings checks before the first paste
- ChatGPT: open Settings, then Data controls, and turn off Improve the model for everyone. Voice mode has its own separate training control, so switch that off too if you dictate listings. Labels change, so look for the equivalent if the wording has moved.
- DeepSeek: read the privacy policy it links at sign-up, use the training opt-out it describes, delete old chats you no longer need, and assume anything pasted is retained.
- Both: use a work email address, not the one tied to your eBay account, so a stray paste cannot be matched to your seller identity.
Scoring a real batch: a filled-in sheet
Below is an illustrative score sheet for the four kitchen items, to show how the totals work. The numbers are invented for the example; yours will differ.
| Item | Tool A (title / specifics / accuracy) | Tool B (title / specifics / accuracy) |
|---|---|---|
| 1. Stand mixer, bowl missing | 2 / 2 / 2 | 2 / 1 / 1 |
| 2. Three steel pans, unbranded | 1 / 1 / 2 | 2 / 0 / 1 |
| 3. Vintage enamel jug | 2 / 2 / 2 | 1 / 0 / 0 |
| 4. Coffee grinder, cracked lid | 2 / 2 / 2 | 1 / 2 / 0 |
| Total (max 24) | 20 | 11 |
In this made-up sheet, the second tool wrote punchier titles on two items but invented specifics on three, and that dominated the result. The lesson worth keeping is the shape: when the totals are close, edit minutes and data handling decide; when one tool invents specifics repeatedly, it is out regardless of style.
Handling the awkward ten percent: photos, buyer questions and returns
Once titles and specifics are settled, sellers usually test two more jobs, and both deserve a rule before you try them.
Describing from photos
Both tools accept photo uploads (ChatGPT reads images you add to a chat, and DeepSeek's app lists photo uploads and a vision mode in its release notes), but a photo is a data source you do not control. A parcel label in the background, a handwritten note, a reflection of your window with a street number on it: all of it travels with the upload. Crop first, then ask the model to read only model numbers and visible damage. Treat what it reads as a draft, because small print on a base plate is exactly where text recognition slips. An illustrative slip: a model reads "CP-250" off the grinder base as "CP-2S0", and an unwary seller lists the wrong model. The fix is a ten-second look at the photo beside the output before you publish.
Answering "does this fit?" questions
Pre-sale questions are the cheapest use of an assistant because they contain no personal data once you paste only the question. A good prompt gives the model your own listing text and the buyer's question with the name removed, and tells it to answer only from the listing:
Answer this buyer question using ONLY my listing text below.
If the listing does not say, reply "I'll check and come back to you".
Keep it under 60 words, friendly, no promises about delivery dates.
LISTING: [paste your own listing]
QUESTION: Does the lid come off for cleaning, and is the hopper plastic or glass?
A well-behaved output either answers from the listing or defers. A badly behaved one answers "plastic" because most hoppers are. Run this prompt through both tools on three real past questions and add the result to your scoring sheet as a fourth column. Deferring is a pass; a confident guess is a fail.
Returns and disputes
Never paste an active dispute, however tempting. Those messages contain names, addresses and order details, and the reply has legal and account consequences. Write these yourself, or write the structure with a placeholder version ("[buyer], thanks for getting in touch about [item]") and fill the details in your own editor.
Checking a listing after it goes live
The test does not end at publish. For the first week of any new workflow, take five minutes at the end of each day to review what you listed. Compare the live title with the one you approved, and check whether any category-specific item specific was left blank or flagged by the listing form. Look at views against comparable older listings that you wrote by hand. Fewer than ten listings is not enough to draw a conclusion about search ranking, so do not credit or blame the assistant for sales on a small sample; you are checking for errors, not measuring performance.
Keep a log of corrections. A simple three-column note (item, what the model got wrong, how you spotted it) tells you within a month which instruction to add to your prompt. Typical entries are a missing "Used", a size given in the wrong unit, or a feature carried over from the previous item because you reused a chat. The log also tells you whether the second tool deserves another try after an update.
Picking a default and writing it down
When the sheet is complete, write a one-paragraph standing decision and keep it with your prompt. For example: "Default assistant: the one with the higher accuracy total. Rule: no buyer data in either. DeepSeek only for public product facts. Re-test next quarter." That sentence saves you re-arguing the choice every time a new model is announced, and it is the sort of rule a helper or a family member working your stock can follow without asking.
What to do with the result
Whichever wins, do not hand it the keys. Keep a pre-publish checklist: title under 80 characters and checked by a counter, every item specific matched to the item, every flaw stated in the description and mirrored in the photos, and a final read for any promotional adjective you did not write. For a deeper condition-and-flaws structure, my eBay description template pairs well with this test. If you list in volume, bulk listing tools change the economics of editing, and multichannel listing covers what changes when the same item goes to other marketplaces with different title limits.
Re-run the test every quarter with a fresh ten items. Both products change often, and your product mix will drift too. Keep the winning prompt in a note, with the rules at the top, so a new tool can be tested in twenty minutes rather than an afternoon.
Questions sellers ask before picking one
Can I paste buyer messages into DeepSeek or ChatGPT?
Strip names, addresses, order numbers and phone numbers first, or leave buyer messages out altogether. If a message needs a reply, paste only the question, such as 'does this fit a 2018 model?', and write the greeting and sign-off yourself. Treat buyer details as off limits for any consumer chat tool.
Do I have to disclose AI-written listings on eBay?
I couldn't find an eBay rule that requires a disclosure line for text you edited and checked yourself, but policies change, so read the current listing policies before you rely on that. Your real obligation is accuracy: the title, condition and item specifics must describe the item in your hands.
Which is cheaper for a small seller?
ChatGPT has a free plan and DeepSeek's chat app is free to download and use, so both cost little or nothing at a part-time seller's volume. Cost rarely decides this. Edit time, accuracy on item specifics and where your item data ends up matter far more than a few dollars a month.
Should I switch tools mid-batch?
No. Pick one for each batch so your prompt, rules and scoring stay comparable. Re-run your ten-item test every few months, because both products update often and last quarter's winner may not be this quarter's.
Further reads
- How to Sync Stock Across Shopify, Amazon and eBay Automatically — Keeping stock right once listings go live.
- How to Write eBay Listings With AI That Sell Faster — The wider listing workflow beyond the comparison.
- AI Listing Mistakes That Can Mislead Buyers, and How to Check — Listing errors that trigger not-as-described claims.
- AI Tools for Resellers: Price Used Stock From Sold-Listing Data — Turn sold-listing comps into price bands by condition, a floor from cost plus fees and an outlier check, with a worked example and ready prompts.
- AI Tools and AI Development: The Complete 2026 Guide — the AI hub, including every tutorial in the AI-for-business series.
Sources: eBay's developer guide to listing titles (80-character maximum), DeepSeek's privacy policy (last updated February 2026), its model card on Hugging Face (MIT licence) and its app-store listing, OpenAI's Data Controls FAQ and image inputs FAQ; all checked November 2026.