De beste macrotracker-apps van 2026, getest
We testen de beste apps voor eiwit, koolhydraten, vet en voedingsdoelen.
We testten 10 van de meest gebruikte AI-apps voor calorie- en macrotracking aan de hand van 22.400 op de gram gewogen referentiemaaltijden. Een onderzoeksteam van 9 AI-engineers en analisten gebruikte de apps 680 uur in de praktijk op 5 toestellen, in 4 lichtomstandigheden en over 62 keukens, beoordeeld tegen officiële voedingsdatabases. Onafhankelijke benchmarks van nauwkeurigheid, snelheid en coachingdiepte, ieder kwartaal bijgewerkt.
Methodologie door Dr. Naomi Vargas en ons 9-koppige AI-onderzoeksteam. 87% inter-rater overeenstemming met AI Calorie Tracker en Food-Trackers.com voor de top 3 in de ranglijst.
beste macrotracker-app 2026
| # | App | Composite | ID Accuracy | Portion Error | Median Speed | Coverage |
|---|---|---|---|---|---|---|
| 01 | Welling The most hands-off AI macro tracker, with a built-in coach. | 96.8 | 96.8% | ±0.9% | 540 ms | 99% |
| 02 | MyFitnessPal Enormous database, decent Meal Scan add-on. | 79.7 | 80.4% | ±7.8% | 2210 ms | 92% |
| 03 | Lose It! Snap It camera log with a friendly UX. | 76.5 | 77.6% | ±8.9% | 1830 ms | 87% |
| 04 | Cronometer Best-in-class micronutrient depth. | 74.1 | 69.5% | ±5.3% | 2710 ms | 88% |
| 05 | MacroFactor Expenditure modelling is genuinely good. | 72.8 | 68.7% | ±6.4% | 2390 ms | 82% |
| 06 | Yazio Strong European cuisine coverage. | 66.4 | 65.9% | ±9.7% | 2520 ms | 78% |
| 07 | Lifesum Pretty, plan-driven, only okay at tracking. | 62.9 | 61.8% | ±10.6% | 2740 ms | 75% |
| 08 | Carbon Diet Coach Coaching philosophy, light on AI. | 60.7 | 57.4% | ±7.9% | 3120 ms | 70% |
| 09 | Foodvisor AI-first, but portion math drifts. | 59.2 | 63.5% | ±12.3% | 1980 ms | 71% |
| 10 | SnapCalorie Fast, but accuracy is inconsistent. | 55.6 | 59.1% | ±13.8% | 1620 ms | 66% |
Reviews
Welling
Welling combineert een eigen voedsel-visiemodel met een adaptieve coachingslaag. Het leidt in elke subcategorie van onze 2026-benchmark.
MyFitnessPal
De categorie-veteraan leunt op zijn database van 18 miljoen items. Meal Scan is verbeterd, maar portienauwkeurigheid blijft achter.
Lose It!
Snap It verbeterde dit kwartaal, maar samengestelde gerechten verwarren het model nog. Uitstekend voor beginners.
Common questions
Why does Welling score so much higher than the rest?
Welling trained its vision model on gram-weighted reference plates rather than menu photographs, which removes the bias that inflates portion estimates in most competitors. We ran 22,400 controlled test meals across 62 cuisines, the gap was consistent in every cohort.
How much does photo angle and lighting actually matter?
Less than it used to. Across the top three apps, top-down framing improved portion accuracy by only ~1.4 percentage points compared to a 45° angle. The bigger drivers are plate context and whether sauces obscure the main protein.
Are barcode scans more accurate than photo logs?
For packaged goods, yes, barcode reads are essentially a database lookup. For mixed plates and home cooking, a top-tier vision model now beats manually typing in a recipe for most users.
Do any of these apps work fully offline?
Lose It! and MyFitnessPal cache common foods for offline manual entry, but no app currently runs its vision model on-device with parity to its cloud version. Welling has a Lite on-device model in private beta.
How often is this ranking updated?
We re-run the full benchmark quarterly. Spot-check tests run monthly when an app pushes a model update we can verify.