Benchmarking Different Airports

Benchmarking Different Airports

Estimated Lesson Time: 40–50 Minutes

Lesson Overview

By now, you’ve created your benchmark flight and learned how to measure performance correctly.

In this lesson, we’re going to explore one of the biggest variables in Microsoft Flight Simulator:

The airport itself.

Not all airports are created equally.

Some airports place enormous demands on your CPU.

Others place greater demands on your GPU.

Some airports are surrounded by photogrammetry, while others are located in relatively simple scenery.

Understanding why airports perform differently is essential if you want to benchmark your simulator fairly and optimise it effectively.

By the end of this lesson, you’ll understand exactly why Heathrow may perform very differently from Innsbruck—even if every graphics setting remains unchanged.

Lesson Objectives

By the end of this lesson you will understand:

Why airport performance varies.

How airport complexity affects your hardware.

The impact of photogrammetry.

Airport object density.

AI traffic.

CPU workload.

GPU workload.

How to compare different airports professionally.

Why Airports Matter

When benchmarking Microsoft Flight Simulator, the airport often has a greater influence on performance than your graphics settings.

Every airport contains a unique combination of:

  • Buildings.
  • Jetways.
  • Ground service vehicles.
  • Lighting.
  • AI aircraft.
  • Static aircraft.
  • Taxiway signs.
  • Ground markings.
  • Terrain.
  • Photogrammetry.

These all require processing by your CPU and GPU.

Changing airport means changing the workload.

This is why professional benchmarking always specifies the exact airport used.

1. Heathrow (EGLL)

Heathrow is one of the busiest and most demanding airports in Microsoft Flight Simulator.

Why?

Heathrow contains:

  • Large terminal buildings.
  • Hundreds of airport objects.
  • Complex lighting.
  • Dense taxiway layouts.
  • Heavy AI traffic.
  • High aircraft density.
  • Nearby London photogrammetry.

CPU Workload

The CPU must process:

  • AI aircraft.
  • Ground vehicles.
  • Airport workers.
  • Glass cockpit systems.
  • Terrain streaming.
  • Object management.

Busy airports often become MainThread Limited.

GPU Workload

The GPU renders:

  • Thousands of visible objects.
  • Terminal glass.
  • Reflections.
  • Dynamic lighting.
  • Volumetric clouds.
  • High-resolution textures.

Typical Result

Expect:

  • Lower FPS.
  • Higher CPU usage.
  • Higher GPU usage.
  • Increased VRAM consumption.
  • More demanding taxi performance.

2. John F. Kennedy International (KJFK)

JFK presents a different workload.

Large terminals combine with the surrounding New York photogrammetry to create a demanding benchmark.

Why It’s Challenging

  • Dense airport layout.
  • Heavy AI traffic.
  • Large surrounding city.
  • Extensive photogrammetry.
  • Complex lighting.
  • Numerous static objects.

CPU Impact

The CPU manages:

  • AI aircraft.
  • Airport systems.
  • Scenery streaming.
  • Building management.
  • Road traffic.

GPU Impact

Rendering:

  • Manhattan skyline.
  • Reflections.
  • Large texture sets.
  • Water.
  • Shadows.
  • Clouds.

This creates one of the most demanding GPU environments in the simulator.

3. Frankfurt (EDDF)

Frankfurt is another excellent benchmarking airport.

It combines:

  • Large terminals.
  • Dense apron layouts.
  • Complex taxiways.
  • Heavy commercial traffic.

Compared with Heathrow, Frankfurt may stress your system differently depending on:

  • Add-ons installed.
  • AI traffic settings.
  • Airport version.
  • Photogrammetry usage.

Professional benchmarking often includes Frankfurt because it represents a busy European hub.

4. Innsbruck (LOWI)

Innsbruck demonstrates that airport performance isn’t determined solely by airport size.

Although the airport itself is relatively small:

The surrounding terrain introduces additional workload.

Terrain

The simulator must render:

  • Mountains.
  • Valleys.
  • Elevation changes.
  • Complex terrain meshes.

GPU Impact

Mountain scenery often increases:

  • Draw distance.
  • Terrain rendering.
  • Shadow calculations.

CPU Impact

Terrain streaming and scenery loading also increase CPU activity.

Innsbruck demonstrates how geography influences performance just as much as airport size.

5. Small General Aviation Airports

Examples:

  • Oxford (EGTK).
  • Gloucester (EGBJ).
  • Small regional airports.

These typically contain:

  • Fewer buildings.
  • Less traffic.
  • Smaller aprons.
  • Minimal ground services.
  • Fewer objects.

Performance Characteristics

Lower CPU workload.

Lower GPU workload.

Reduced VRAM usage.

Higher FPS.

This makes GA airports useful for baseline testing but less representative of demanding airline operations.

Photogrammetry

Photogrammetry recreates real-world cities using aerial scanning.

Rather than simple 3D buildings, the simulator loads highly detailed models.

Examples:

  • London.
  • New York.
  • Paris.

Why Is It Demanding?

Photogrammetry increases:

  • CPU calculations.
  • GPU rendering.
  • VRAM usage.
  • Streaming bandwidth.
  • Storage activity.

Flying near major cities can reduce performance significantly compared to rural areas.

Airport Density

Airport density refers to the number of visible objects.

Examples include:

  • Terminal buildings.
  • Jetways.
  • Hangars.
  • Fuel trucks.
  • Ground service equipment.
  • Taxiway signs.
  • Lighting.
  • Static aircraft.

Higher density means:

More objects to process.

More draw calls.

More work for both CPU and GPU.

AI Traffic

AI traffic affects both realism and performance.

Every AI aircraft requires:

  • Flight calculations.
  • Taxi logic.
  • ATC interaction.
  • Animation.
  • Lighting.
  • Navigation.

Increasing AI traffic often raises CPU usage more than GPU usage.

Busy airports with heavy AI traffic frequently become MainThread Limited.

CPU Load

The CPU manages:

  • AI.
  • Airport logic.
  • Ground traffic.
  • Terrain streaming.
  • Aircraft systems.
  • Glass cockpits.
  • Object management.

Large international airports place heavy demands on the MainThread.

GPU Load

The GPU renders:

  • Buildings.
  • Clouds.
  • Shadows.
  • Reflections.
  • Terrain.
  • Lighting.
  • Textures.
  • Water.

High object counts and large cities increase GPU utilisation significantly.

Comparing Airports

Imagine these benchmark results:

Heathrow

Average FPS:

58

MainThread:

Limited

GPU:

94%

Innsbruck

Average FPS:

74

MainThread:

Occasionally Limited

GPU:

98%

Oxford

Average FPS:

112

GPU:

88%

MainThread:

Minimal limitation

These results don’t mean Oxford is better optimised.

They simply reflect different workloads.

Always compare airports within the context of their scenery complexity.

Common Mistakes

Comparing FPS between completely different airports.

Ignoring photogrammetry.

Changing AI traffic during benchmarks.

Forgetting weather influences.

Assuming all airports stress the GPU equally.

Believing airport size alone determines performance.

Student Exercise

Today you’re going to compare three different airports.

Step 1

Choose three airports.

For example:

  • Heathrow (large international hub).
  • Innsbruck (mountain airport).
  • A local GA airport.

Use the same:

  • Aircraft.
  • Graphics settings.
  • Weather preset.
  • Time of day.

Step 2

Fly the same benchmark pattern at each airport.

Record:

  • Average FPS.
  • Minimum FPS.
  • 1% Lows.
  • GPU utilisation.
  • VRAM usage.
  • MainThread status.
  • GPU Limited status.
  • Overall smoothness.

Step 3

Compare your results.

Ask yourself:

  • Which airport placed the greatest load on your CPU?
  • Which airport produced the highest GPU utilisation?
  • Did photogrammetry noticeably affect performance?
  • Which airport felt the smoothest to fly?
  • How did AI traffic influence the results?

Student Checklist

Three airports selected.

Same aircraft used.

Same weather used.

Same graphics settings maintained.

Benchmarks completed.

CPU behaviour analysed.

GPU behaviour analysed.

Results compared.

Lesson Summary

Congratulations.

You now understand why airport selection is one of the most important variables in Microsoft Flight Simulator benchmarking.

Remember:

  • Airports vary significantly in complexity and workload.
  • Large international hubs generally place heavier demands on both the CPU and GPU.
  • Photogrammetry increases scenery detail but also increases rendering and streaming demands.
  • AI traffic, airport object density and surrounding scenery all influence performance.
  • Benchmark results are only meaningful when the testing environment remains consistent.
  • Understanding how different airports affect your hardware will help you interpret benchmark results accurately and choose realistic test scenarios for future optimisations.

Knowledge Check

  1. Why do different airports produce different benchmark results?
  2. How does photogrammetry affect CPU and GPU workload?
  3. Why are large international airports often MainThread limited?
  4. How does airport object density influence performance?
  5. Why does AI traffic primarily affect CPU performance?
  6. Why can Innsbruck be demanding despite being a relatively small airport?
  7. Why are GA airports useful for benchmarking?
  8. Why should you avoid comparing FPS between completely different airports without considering scenery complexity?
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