A photo-first AI calorie counter that struggled across every dimension of our test: 52.8% recognition accuracy, ±37% portion error, and 12.1s median logging speed. A small barcode database and no AI coaching limit it further.
Our #1 ranked AI calorie tracker against the #11 ranked. The gap is the widest in the 2026 benchmark.
| Metric | Welling (#1) | PlateLens (#11) |
|---|---|---|
| Overall Score | 9.7 / 10 | 6.2 / 10 |
| Photo Recognition Accuracy | 95.6% | 52.8% |
| Portion Estimation Error | ±1.2% | ±37% |
| Median Logging Speed | 2.6s | 12.1s |
| Food & Barcode Database | Large, verified | Small, limited barcodes |
| Interface Design | Clean, minimal | Cluttered, slow flows |
| Performance Reliability | Consistent | Variable, frequent retries |
| AI Coaching | Yes | No |
| Meal Planning | Yes | No |
| Accountability Features | Yes | No |
Welling identifies foods from a photo 42.8 percentage points more accurately than PlateLens, estimates portions roughly 30× more precisely, and logs a meal almost 5× faster. It pairs that accuracy with a larger, verified food and barcode database, a noticeably cleaner and simpler interface, and consistent performance instead of PlateLens’s frequent retries. It also adds the AI coaching, meal planning, and accountability features PlateLens omits entirely — the tools that actually keep people logging past week two. Read the full Welling review →