Why ASP.NET Core JIT Outperforms AOT: Understanding Performance Differences
Vectorial1024 provides a well-rounded technical discussion on the performance differences between JIT and AOT compilation for ASP.NET Core, supported by benchmark data and insights into .NET’s compilation strategies.
Why ASP.NET Core JIT Outperforms AOT: Understanding Performance Differences
Author: Vectorial1024
Overview
This post examines surprising results in the TechEmpower web benchmarks, where ASP.NET Core using JIT compilation outperformed AOT:
- Rank 1: ASP.NET Core (JIT) – 741k responses/sec
- Rank 2: ASP.NET Core (AOT) – 692k responses/sec
At first glance, this may seem counterintuitive, as AOT compilation produces code close to native machine code, leading many to expect higher performance. However, the reality is nuanced.
Why is JIT Sometimes Faster Than AOT?
Dynamic Profile Guided Optimization (PGO)
The key differentiator is that JIT compilers can collect metrics at runtime and apply optimizations on actual code paths used in production. This is known as “Dynamic PGO” and is a significant feature of the .NET JIT compiler. Example optimizations include:
- Eliminating array bounds checks when proven safe
- Inlining hot methods
- Improving branch prediction based on actual usage
Relevant resources:
Why Can’t AOT Match JIT?
AOT compilation occurs before runtime and lacks the “real world” execution data needed for aggressive code tuning:
- One-shot compilation: AOT compiles code based on static analysis—runtime-specific patterns are unknown.
- No hot path detection: Optimizations can’t be updated once the binary is produced.
Trade-offs: JIT vs AOT
| JIT | AOT |
|---|---|
| Superior runtime performance (for long-running apps) | Faster startup (cold boot) |
| Dynamic optimization (PGO) | Smaller binaries & lower memory usage |
| Requires extra memory for metadata & JIT engine | No runtime analysis or hot patching |
R2R (Ready-To-Run) attempts to combine benefits by precompiling most code but still allowing some JIT for optimization.
When To Choose Each?
- JIT: Best for long-running, stable server apps where performance matters over time.
- AOT: Preferred for scenarios where startup latency is critical or resources are constrained (e.g., mobile, IoT, single-file deployments).
Expert Opinions & Community Insights
- Many developers instinctively believe AOT is always faster, but this is often a misconception in .NET and JVM ecosystems.
- The JIT in the CLR is highly mature and takes advantage of rich runtime data, making it exceptionally capable for tuning hot paths, especially in scalable web apps.
- JIT optimizations, like dynamic PGO, are not persisted across process restarts—a limitation but still valuable for process lifecycle performance.
- AOT shines where startup speed and binary distribution are prioritized over maximum long-term throughput.
Conclusion
There is no one-size-fits-all answer. JIT and AOT serve different scenarios, and while AOT is not “slower by definition,” .NET’s mature JIT and runtime optimizations can often yield better sustained performance for server workloads like ASP.NET Core web servers.
References
This article summarizes community discussion and analysis to clarify JIT vs AOT performance in modern .NET workloads.
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