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Table of Contents
Comparison of CPU usage under high concurrency
Memory footprint: lightweight vs flexibility
The trade-off between development efficiency and performance
Home Backend Development Golang Resource Consumption (CPU/Memory) Benchmarks for Typical Golang vs Python Web Services

Resource Consumption (CPU/Memory) Benchmarks for Typical Golang vs Python Web Services

Jul 03, 2025 am 02:38 AM

Golang usually consumes less CPU and memory than Python when building web services. 1. Golang's goroutine model is efficient in scheduling, has strong concurrent request processing capabilities, and has lower CPU utilization; 2. Go is compiled into native code, does not rely on virtual machines during runtime, and has a smaller memory footprint; 3. Python has a greater CPU and memory overhead in concurrent scenarios due to GIL and interpretation execution mechanism; 4. Although Python has high development efficiency and rich ecosystem, it consumes a high resource, which is suitable for scenarios with low concurrency requirements.

Resource Consumption (CPU/Memory) Benchmarks for Typical Golang vs Python Web Services

If you want to know the difference in CPU and memory consumption between Golang and Python when building web services, the most direct answer is: Golang usually performs better in resource efficiency, especially in high concurrency scenarios.

Resource Consumption (CPU/Memory) Benchmarks for Typical Golang vs Python Web Services

Comparison of CPU usage under high concurrency

Go (Golang)'s goroutine model makes it naturally suitable for handling large numbers of concurrent requests. Each goroutine has very small overhead, only about 2KB of memory usage, and is very efficient in scheduling.

Resource Consumption (CPU/Memory) Benchmarks for Typical Golang vs Python Web Services

Python is highly restricted in multithreaded concurrency due to the existence of global interpreter locks (GILs). While GIL can be bypassed by multiple processes, this leads to higher CPU context switching overhead and greater memory footprint.

Let's give a simple example:

Resource Consumption (CPU/Memory) Benchmarks for Typical Golang vs Python Web Services
  • A Go-written HTTP service may maintain CPU usage at around 30% at 1000 QPS.
  • Under the same load, services implemented with Flask or Django may use more than 60% of the CPU, especially without asynchronous support.

This is not to say that Python is bad, but the language mechanism determines its performance ceiling in some scenarios.


Memory footprint: lightweight vs flexibility

Go compiles to native code and does not require an extra virtual machine or interpreter at runtime, so it usually has a low memory footprint. A typical Go Web service may only occupy dozens of MB of memory when it is idle.

Python needs to explain execution, dynamic types, and runtime libraries that rely more on, and memory usage is relatively high after startup. Even for small Flask applications, the initial memory may reach 50MB to 100MB, and it will grow faster as the number of requests increases.

Some actual observation data can be referenced:

  • Go Gin framework: With 1000 concurrent requests, memory occupies about 80MB
  • Python Flask (Werkzeug): It may reach 300MB to 400MB under the same conditions
  • If you use gunicorn multi-worker mode, the memory can easily exceed 500MB

Of course, using asynchronous frameworks such as FastAPI or Tornado can alleviate some of the problems, but overall it is still not as lightweight as Go.


The trade-off between development efficiency and performance

Although Go has obvious performance advantages, Python still has advantages that cannot be ignored in terms of development efficiency and ecological richness. For example:

  • Rapid prototyping: Python faster
  • Data processing, machine learning integration: Python ecosystem is more mature
  • Team Skill Matching: If the team is familiar with Python, it is expensive to change languages

Therefore, when choosing a language, you should not only look at performance indicators, but also combine project needs and team background.

If your application does not expect high concurrency or is not sensitive to response time, Python is perfectly competent. But if you want to support large-scale access, microservice architecture, or want to reduce server resource expenditure, Go is a more suitable choice.


Overall, Golang is more efficient than Python in terms of CPU and memory resource utilization, and is especially suitable for high concurrency and low latency Web services. The advantages of Python lie in its rapid development and rich library support, but it is indeed higher in resource consumption. Which language to choose depends on the specific scenario.

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