The biggest lie in the software industry is that no-code has to be slow. For years, developers and enterprises have paid a "no-code tax," trading performance for ease of use. At CodeZero, we decided to kill that trade-off.
To prove it, we staged a battle against n8n, the current industry standard. We didn't use theoretical models. We used an Apple M3 MacBook Air and identical workflows on both platforms. The result is that CodeZero isn’t just an alternative, it’s a generational leap in efficiency.
The setup: identical logic, no excuses
A benchmark is only as good as its transparency. We mirrored the exact same logic on both platforms: a simple HTTP webhook that returns a 200 OK response. By removing external variables like API delays or database latency, we isolated the raw overhead of the execution engines themselves.
Using Docker, we capped resources at three tiers (1.0, 0.5, and 0.25 vCPU) and used k6 to simulate high-concurrency traffic.
1.0 vCPU: 12x more throughput
Even when given a full core, legacy architecture hits a wall. While n8n struggles to manage its own internal processes, CodeZero focuses entirely on moving data.
The data shows that CodeZero scaled effortlessly to 2,147 req/s, while n8n peaked at a mere 177 req/s. This gap represents the difference between a system that thrives under pressure and one that merely survives.
At 200 concurrent users, n8n delayed for 1.1s while CodeZero stayed at 0.1s. In a production environment, this means you can handle an entire marketing spike on a single core that would have crashed a legacy setup. CodeZero is 11x faster out of the gate.
0.5 vCPU: 20x higher efficiency
Most cloud instances run on limited resources to save costs. This is where CodeZero’s lean architecture turns into a massive financial advantage for any business scaling its automation.
In this mid-tier setup, CodeZero maintained a rock-solid 1,279 req/s. In contrast, n8n’s throughput dropped to 64 req/s. The efficiency multiplier here is 20x, meaning your hardware is significantly more productive with CodeZero.
This is where it gets dangerous for legacy systems. The response times for n8n spiked to 3.0s, which is unacceptable for modern real-time applications. CodeZero held steady at 0.2s, ensuring that the end-user never feels the load.
0.25 vCPU: the 17-second collapse
We pushed both engines into a resource-starved environment to see which one would break first. The results were staggering and highlight the fundamental architectural differences.
Under extreme pressure, n8n gasped for air at 10 req/s. CodeZero still pushed a functional 339 req/s. This proves that CodeZero can handle significant traffic even on the cheapest possible entry-level hardware.
The latency results here are the final breaking point. n8n exploded to 17.6s, which is effectively a total system failure. CodeZero finished the same task in 0.6s. CodeZero is 29.3x faster when resources are tight, keeping the lights on while others fail.
Why the gap is so large
Since the workflows were identical, this isn't about the complexity of the tasks. It is about the plumbing. Legacy tools carry massive internal bloat and require hundreds of megabytes of RAM just to sit idle.
CodeZero was engineered with a zero-bloat philosophy and a 160x smaller memory footprint. The M3 chip spends its energy executing your logic rather than managing the engine's weight. We optimized the concurrency model so that thousands of requests do not cause the system to choke on context-switching.
Stop paying the no-code tax
The era of slow, resource-heavy automation is over. The data from these six scenarios proves that with the right architecture, no-code is as fast as raw code. By switching to CodeZero, you can scale 30x further on your existing hardware and slash cloud costs by deploying on significantly smaller instances. You deliver instant responses that never timeout, even under heavy load.
No-code is officially fast. Welcome to the future of execution.
