Benchmark
Finding the best AI
for product descriptions.
305 head-to-head votes across 14 real products. Voters chose between two descriptions without knowing which model wrote each.
Goal
Our goal was to build an API that lets you easily implement an image-to-description pipeline for a second-hand marketplace/exchange, specifically for the "TBZ Tauschhütte".
305
Human votes
14
Products tested
8
Models compared
ELO ranking
Average ELO across all products. Starting ELO is 1400.
Win rate
Head-to-head matchup win percentage across all products.
46W / 6L
41W / 16L
36W / 19L
33W / 19L
30W / 15L
30W / 36L
16W / 51L
1W / 71L
Votes won
Total times each model was preferred by voters.
Pipelines
Splitting image analysis and copywriting across two models.
Our idea with pipelines was that we could leverage the image parsing capabilities of one model with the writing competence of another. Our testing revealed that even though it is possible and produces great results, it doesn't beat out just using a model directly. We speculated that it's because a lot of context is lost when the data is handed over from one model to another.
Performance by product
ELO per model per product. Colors show relative rank within each row — green beats red.
| Product | Gemini Flash | Gemini→Claude | GPT-5 Nano | Claude Sonnet 4 | GPT-4o Mini→4o | Qwen 3.5 | Mistral Small | GPT-4o |
|---|---|---|---|---|---|---|---|---|
| Rollschuhe | 1498 | 1405 | 1453 | 1404 | 1426 | 1328 | 1357 | 1329 |
| Cars Carrara Bahn | 1497 | 1385 | 1383 | 1416 | 1374 | 1401 | 1416 | 1328 |
| Radon Trekkingrad Solution Sport 3 | 1484 | 1403 | 1381 | 1430 | 1414 | 1380 | 1357 | 1351 |
| Schreibtisch | 1431 | 1474 | 1429 | 1377 | 1427 | 1370 | 1326 | 1366 |
| Kinderwagen | 1460 | 1431 | 1428 | 1416 | 1416 | 1382 | 1343 | 1324 |
| Petroleum Lampe | 1457 | 1416 | 1417 | 1404 | 1442 | 1394 | 1341 | 1329 |
| Keramik-Wanduhr | 1430 | 1432 | 1455 | 1356 | 1368 | 1445 | 1383 | 1331 |
| Zangen Set | 1419 | 1440 | 1443 | 1384 | 1455 | 1408 | 1357 | 1294 |
| Waschmaschine | 1413 | 1428 | 1432 | 1384 | 1431 | 1416 | 1382 | 1314 |
| Roter Sessel | 1443 | 1399 | 1385 | 1444 | 1416 | 1415 | 1356 | 1342 |
| Monopoly Bremen | 1399 | 1417 | 1448 | 1447 | 1412 | 1383 | 1395 | 1299 |
| Bosch Bohrmaschine | 1413 | 1442 | 1456 | 1458 | 1386 | 1385 | 1322 | 1338 |
| Bowleset mit Tassen | 1404 | 1482 | 1348 | 1458 | 1415 | 1383 | 1366 | 1344 |
| Pegasus Fahrrad | 1429 | 1409 | 1384 | 1446 | 1433 | 1413 | 1385 | 1301 |
Limitations
Due to our limited budget, we were only able to test and select a limited number of models. This means that there might be a better model out there, but using it would not be economically viable.
Furthermore, we had to carefully pick out what items we tested, we based our selection on what would usually be found in the "Tauschhütte" and on second-hand marketplaces like "kleinanzeigen.de". In combination with the fact that we didn't test specific model-to-product combinations, it is possible that specific products would perform better for product types than our overall best config (Gemini Flash).
Methodology
ELO rating
All models start at 1400. Each vote adjusts both scores with the standard ELO formula (K=32).Blind voting
Voters see two descriptions without knowing which model wrote each. They pick the one they prefer.Coverage
Every possible pair of descriptions for each product was shown as a matchup.Snapshot: 2026-06-03 · 305 votes · 14 products