Which Calorie Tracker App Is Fastest in Real Life? A 7-Day Test

Which calorie tracker app is fastest in real life? We tested MyNetDiary, MacroFactor, MyFitnessPal, and Cronometer over 7 days with 127 food entries to find out.

Introduction

MacroFactor's Food Logging Speed Index (FLSI) is an interesting benchmark, and we agree that speed genuinely matters for logging adherence. The faster and easier it is to log your food, the more likely you are to stick with it. That's why we took their methodology seriously—and then asked: does it reflect how people actually use calorie tracker apps?

The limitation we found: FLSI tests isolated, simplified workflows—logging a few foods as if each is brand new. But that's not how real food logging works.

Consider the foods FLSI used for testing: "greek yogurt," "honey," "banana," and "peanut butter"—short, generic names that are easy to find in any database. Real users log foods like "Total 0% greek yogurt by Fage" and "Raw & unfiltered southwest honey by Local Hive"—specific products with multi-word names that test an app's search intelligence far more rigorously.

The reality: People don't log food the way FLSI tests it. Real users eat the same breakfast several days a week, re-scan that favorite protein bar, log a large variety of foods (many prepackaged), have recurring meals throughout the week, and eat the same foods in different amounts across different meals.

Our thesis: A more meaningful speed test measures total effort across a realistic week of eating—with real foods, real brands, and real usage patterns—where smart apps reward users with easy, efficient food logging, helping them stick with food tracking and reach their goals.

The Problem with Isolated Workflow Testing

What FLSI measures:

• Number of taps for two single-food searches
• Logging with a multi-add function for two foods
• Number of taps for one barcode scan
• Number of taps for one quick-add

What it misses:

• Logging a limited number of foods per workflow—real meals have multiple items
• Frequency effects: If you eat Greek yogurt 5x this week, does the app remember and prioritize the food?
• History-based suggestions: Does the app learn your patterns and surface the right foods first?
• Combined workflows: Real logging sessions involve search + scan + recent items together
• Quality and intelligence of database searches for non-trivial, multi-word food names
• Efficiency of entering/editing serving types and amounts

The core argument: The app that requires fewer taps for a realistic week is easier and faster for users in sustained, real-world use.

Our Methodology: The Real-World Logging Speed Index

The Test Setup

We took an anonymized, real user's first week of food logging in MyNetDiary. The log contained a natural mix of food searches, barcode scans, various meal types (breakfast, lunch, dinner, snacks), and foods that repeated throughout the week.

To keep the comparison apples-to-apples with FLSI methodology:

• No AI food scanning used
• No quick-add calories used
• No shortcuts used: We did not use features like "copy all of yesterday's foods," meal templates, or saved recipes—only search and history screens and barcode scans, the same workflows FLSI tests
• No penalty for missing foods: We are measuring logging speed, not database quality. If a food wasn't found after searching the same terms, we selected a similar food without penalizing the action count.
• All apps were configured to the fastest settings, with multi-add enabled
• Premium versions used where applicable to test each app at its best
• Starting point: In all apps, each meal's logging was initiated from the app dashboard—simulating a user who opens the app after eating, logs their meal, and closes the app before the next meal
• Device: iPhone Air running iOS 26
• App versions: All apps were downloaded from the App Store in January 2026
• No bias toward any app: We documented every step

The Dataset

• 127 total food entries logged across seven days
• 27 meals (7 days × 4 meals each, but no snacks on day 1)
• 4.7 average food entries per meal
• 70 unique foods
• 13 barcode scans
• No custom foods or recipes—only foods from the built-in databases

How We Counted Actions

Each tap counted as one action. Scrolls counted as a single action regardless of how many repeated scrolls were needed to find a food (e.g., scrolling through 20 results = 1 action).

Note: This counting method is conservative—scrolls actually require more effort and time than taps since you must scroll, then read the results. This approach benefited MyFitnessPal and Cronometer (see History Mode in the Results section).

Search Replication

MyNetDiary saves each user search, so we were able to replicate how our original user searched for each food—what words were used by him or her to search for specific foods.

If another app showed the required food in fewer terms or taps than the original user search recorded in MyNetDiary, we used this smaller number for the other app. If, after entering the original search string, the required food was not in the first couple of screenfuls of search results, we resumed typing additional words to find the required food and recorded the final count of taps/actions—but we did not count the actions of our result-scrolling attempt and return to search, to avoid penalizing the other app.

We used predictive type panels or lists as much as possible to minimize typing. MyFitnessPal has two—one above the keyboard and a "Suggested Searches" list below the search box.

Our Commitment to Fairness

We tried to make the comparison as fair as possible, avoiding penalization as much as possible. Sometimes this meant applying stricter standards to MyNetDiary by using the original search as-is, while using an optimized search in other apps if it took fewer actions than the original search.

The Effort Involved

Logging and carefully recording each and every action for 127 food entries is very laborious compared to FLSI, where only a few foods were logged. That's why we tested only a few apps compared to FLSI by MacroFactor—MyNetDiary, MacroFactor, and two of the most popular calorie counter apps on the App Store: MyFitnessPal and Cronometer.

This comprehensive approach, however, reveals real-world patterns that isolated tests cannot capture.

Disclaimer: Actual results when reproducing this test may vary due to continuously updated databases, foods and serving types added or removed, and changes in database search algorithms.

Results

The Bottom Line

• MyNetDiary: 711 actions to log all 127 food entries
• MacroFactor: 877 actions (~23% more than MyNetDiary)
• Cronometer: 1,003 actions (~41% more than MyNetDiary)
• MyFitnessPal: 1,035 actions (~45% more than MyNetDiary)

Total Actions to Log One Week

How Our Results Compare to FLSI Rankings

Our real-world test, using a different methodology, produced different rankings than FLSI:

• MyNetDiary was the most efficient app in our test (#2 in FLSI)
• MacroFactor was second in our test (#1 in FLSI)
• Cronometer scored better than MyFitnessPal in our test, unlike FLSI where MyFitnessPal was ahead of Cronometer

These differences highlight how isolated workflow tests can produce different results than real-world usage patterns.

Meal-by-Meal Breakdown (27 meals total)

• MyNetDiary first or tied for first: 22 meals
• MacroFactor first or tied for first: 4 meals
• MyFitnessPal first or tied for first: 4 meals
• Cronometer first or tied for first: 2 meals

Search-As-You-Type Matters

Search-as-you-type lets you see the required food as soon as you've typed the minimal number of characters. In our testing, only MyFitnessPal lacked this feature entirely. Cronometer has search-as-you-type, but we observed it was slower than MyNetDiary and MacroFactor—displaying a wait indicator, clearing the screen, and refreshing results.

History Mode: Giving MyFitnessPal and Cronometer the Benefit of the Doubt

To give the minimal number of actions to MyFitnessPal and Cronometer, we used "history" mode for previously logged foods. Any food logged earlier in the week was counted as two actions: one "scroll" and one tap on "plus" (or "check" in Cronometer). Subsequent selections of other foods from history were counted as one action (plus or check), as if no scroll needed.

By day 5, scrolling and skimming through 50+ food names in history to find the right one was taking more time than simply typing a few characters from the food name—but we stuck with history mode because it counted fewer actions for MyFitnessPal and Cronometer.

For both MyNetDiary and MacroFactor, we used character typing and thus counted more actions, since typing takes less physical time and effort to narrow down the food required than scrolling through a large list of foods.

Even with this handicap, MyNetDiary and MacroFactor counted fewer actions overall.

MacroFactor Observations

Missing Foods

10 of the 70 foods were not found in MacroFactor's database at the time of testing. As with other apps, we selected a similar food without penalizing the action count.

No Meal Organization

MacroFactor does not use the concept of meals (like breakfast, lunch, or dinner), recording food entries on a timeline instead. The other three apps organize foods by meals and thus needed one extra tap to select a meal compared to "meal-less" logging in MacroFactor. This saved MacroFactor 27 taps—one for each of the 27 meals in the test.

MyFitnessPal Observations

Complete Database

MyFitnessPal had all 70 foods in the database.

The Duplicate Food Problem

Beyond overall lower efficiency, we observed that MyFitnessPal's search results included many duplicate food entries. This sometimes made it difficult to find a specific product variant using the words the user originally typed, requiring additional search terms.

Example: The original user searched "White Cheez" to find baked crackers and log 15 crackers. In MyFitnessPal, five screens of results showed "white cheez it" and "white cheddar" variations—but no baked crackers. We had to return to search and type "baked" to find the correct item.

Note: We did not penalize MyFitnessPal for those five wasted scrolls. Our results record this as if the user typed "white cheez baked" from the start—giving MyFitnessPal the benefit of the doubt.

Limited Serving Types

In our testing, many foods in MyFitnessPal had a limited number of serving types, which can make it difficult to enter the correct amount. Example: Organic Blueberries by Publix did not have tablespoon as a serving option—only cups. We had to enter 1/8 cup instead to record 2 tbsp. This may require users to do mental math or accept less precise logging.

Loose Search Matching

In our testing, MyFitnessPal did not always return results containing all search terms, sometimes prioritizing results that are popular but don't contain all the search words. Example: When searching for "melon liquid IV," the first few screenfuls of results only showed foods with "liquid IV"—no melon. We had to select a different food than originally searched.

No Search-As-You-Type

MyFitnessPal does not display results as you type—you must hit the "Search" button to see results. If the food you need doesn't appear, you have to return to search and continue typing. This requires users to estimate how much to type before searching: you may stop typing too early and need to return to search, or you may type more characters than strictly necessary. Apps with search-as-you-type let users stop typing the moment they see the right food, saving keystrokes.

Cronometer Observations

Limited Serving Sizes and No Fraction Support

In our testing, Cronometer often had a limited number of serving sizes and did not support fractions—only decimals. Example: To enter "15 crackers" when the only serving size available was "26 crackers," we had to use a calculator to determine the decimal fraction (0.6 in this case).

Note: We did not penalize Cronometer for calculator usage, although this makes it difficult to enter accurate amounts in real life.

Missing Foods

4 of the 70 foods were not found in Cronometer's database at the time of testing. As with other apps, we selected a similar food without penalizing the action count.

Feature Spotlight: What Drives Real-World Speed

Database Search Intelligence

How well does the app handle multi-word, non-trivial food names? How does the app rank results—exact matches first, or buried under branded products?

Recent Foods Placement & Logic

Where does the app surface recently logged items? How many taps to access them? Does it learn time-of-day patterns?

Amount Entry Efficiency

How many taps to change a serving size? Does the app make common adjustments easy?

What This Means for Users

• Real-world efficiency diverges significantly between calorie tracker apps
• The best food tracker apps learn your patterns and deliver compounding time savings
• Intelligence of database searches matters—finding the right food quickly adds up over hundreds of food entries
• Efficiency of selecting serving types and editing amounts makes a noticeable difference meal after meal
• The app that feels fastest on a single food entry may not be the best calorie counter across a week of real use

Methodology Notes: Transparency

In the interest of full transparency, we are making available full data spreadsheet with all foods, food searches, servings and amounts.

Download the full data spreadsheet here.

Conclusion

Speed matters, but sustained speed matters more. The best calorie tracker app isn't the one that's fastest on day one—it's the one that's fastest on day 30.

MyNetDiary's design and algorithms were crafted for real-world, long-term efficiency. Isolated workflow tests tell part of the story; a week in the life tells the rest.

The data: Over a real week of logging, MyNetDiary required 23% fewer actions than MacroFactor, 41% fewer than Cronometer, and 45% fewer than MyFitnessPal—and was first or tied for first in 22 of 27 meal comparisons.

When choosing a calorie tracker app, consider not just how fast it is to log a single food, but how efficiently it will help you log hundreds of foods over weeks and months of consistent tracking. That's where real-world speed makes the difference.

About This Study

This comparative study was conducted by MyNetDiary in January 2026. While we have made every effort to ensure fair and accurate testing, readers should be aware that MyNetDiary has a commercial interest in these results. We welcome independent replication of our methodology and have made our complete dataset available for verification. All trademarks mentioned are the property of their respective owners. App features and performance may have changed since this testing was conducted.

Still new to MyNetDiary? Learn more today by downloading the app for FREE.

Check out PlateAI, our new AI-powered diet app at PlateAI.com

Tracking & MyNetDiary->App Reviews