k6 vs Locust: JavaScript scripts or Python users?

k6 and Locust are both open source tools that keep a load test as code in your repository, and either one will load test an HTTP API well. Pick Locust if your team writes Python and wants plain Python for test logic. Pick k6 if you write JavaScript, want pass/fail thresholds built in, or need a test that holds an arrival rate.

The facts in this k6 vs Locust comparison come from each project’s own documentation and repository, checked on 13 October 2026.

What is the difference between k6 and Locust?

The main difference is the language you write tests in. k6 runs JavaScript in a compiled Go program, while Locust runs your Python code and builds on gevent for many concurrent users.

k6 installs as a package or a standalone binary with no other runtime. It also runs .ts files, though its TypeScript support strips the types without checking them. Locust installs with pip install locust, and its What is Locust page says tests are plain Python that you keep in version control like any other code (checked on 13 October 2026).

How do you write the same test in each tool?

Both express the test as a short program. Here is a test with 50 users for five minutes that fails if the 95th percentile tops 500 ms or more than 1% of requests fail.

In k6 the goals are part of the script, as thresholds:

import http from "k6/http";
import { sleep } from "k6";

export const options = {
  vus: 50,
  duration: "5m",
  thresholds: {
    http_req_duration: ["p(95)<500"],
    http_req_failed: ["rate<0.01"],
  },
};

export default function () {
  http.get("https://staging.example.com/api/users");
  sleep(1);
}

In Locust the user is a class, and the same goals go in a listener, following the pattern in the headless mode docs:

import logging
from locust import HttpUser, between, events, task


class ApiUser(HttpUser):
    wait_time = between(1, 2)

    @task
    def list_users(self):
        self.client.get("/api/users")


@events.quitting.add_listener
def _(environment, **kw):
    stats = environment.stats.total
    if stats.fail_ratio > 0.01:
        environment.process_exit_code = 1
    elif stats.get_response_time_percentile(0.95) > 500:
        environment.process_exit_code = 1

Run them with k6 run script.js and locust -f locustfile.py --headless -u 50 -r 10 -t 5m --host https://staging.example.com (checked on 13 October 2026).

How do k6 and Locust model load?

k6 supports both workload models, while Locust describes load as a fixed number of users. In k6 you choose the model through the executor, and in Locust through the user count and wait time.

k6 has six executors. Four are closed-model, where a virtual user starts its next iteration only when the last one finishes, and the two arrival-rate executors are open-model, where iterations start independently of how long earlier ones take. Locust’s locustfile guide says wait time can only constrain throughput and cannot launch new users to reach a target rate (checked on 13 October 2026).

If your goal is “300 requests arrive every second whatever the response time”, k6 can express that directly. Our guide to the open vs closed workload model explains when each model fits.

How do k6 and Locust decide whether a test passed?

k6 has pass/fail criteria as a core feature, and Locust leaves most of it to your code. A failed k6 threshold ends the run with a non-zero exit code, and abortOnFail stops the test the moment it fails.

Locust exits with code 1 if any request failed. For limits on the failure ratio, the average or the 95th percentile, its docs show a listener like the one above that sets the exit code yourself (checked on 13 October 2026). Our guide to pass/fail criteria for load tests covers how to pick the limits.

Which protocols does each tool cover?

k6 ships four protocols and a browser module, while Locust ships HTTP and HTTPS and lets you wrap any Python client for the rest.

k6 lists HTTP/1.1, HTTP/2, WebSockets and gRPC as built-in protocols, with more through xk6 extensions, and a browser module that drives a Chromium-based browser. Locust’s page on other systems says it comes with built-in support only for HTTP/HTTPS but can be extended to test almost any system, by wrapping a protocol library and reporting each call as a request. The library has to cooperate with gevent (checked on 13 October 2026).

How do you run a bigger test than one machine can generate?

Locust scales with a master and workers, and k6 with a Kubernetes operator or a hosted service. Both can split one test across many machines.

The Locust distributed docs say one process can make more than a thousand requests per second for a simple test plan, so larger tests run one worker per processor core across as many machines as needed. The k6-operator splits one test across several k6 instances in a Kubernetes cluster, and Grafana Cloud k6 is the hosted route (checked on 13 October 2026).

There is a third route for k6 scripts. LoadFocus, which publishes this site, runs k6 scripts from 25 cloud regions, with the users and duration taken from the test’s settings. Its script validator warns that arrival-rate scenarios run there with a fixed number of users, so an open-model script does not hold its arrival rate on LoadFocus. LoadFocus does not run Locust: it runs k6 scripts and JMeter test plans only.

What reports do you get?

k6 prints an end-of-test summary and can export an HTML report from its web dashboard. Locust shows live charts in its web UI and writes files on request.

k6’s end-of-test summary goes to the terminal, and its web dashboard exports a self-contained HTML report when you set K6_WEB_DASHBOARD_EXPORT. Locust serves a web UI on port 8089 with live charts, and its configuration reference lists --csv, --html and --json output (checked on 13 October 2026).

Which one should you choose?

Locust fits Python teams, and k6 fits teams that want built-in thresholds and an open workload model. Protocols and scaling settle most other cases.

Choose Locust instead of k6 when your team writes Python and wants loops, branches, generated data and its own API client in plain Python, when you want to reuse Python libraries for a protocol, or when you want a web UI with live charts to explore a system. Choose k6 instead of Locust when your team writes JavaScript or TypeScript, when thresholds should fail a CI build and stop a bad run early, when you need an arrival rate held constant, or when you want gRPC and browser tests in the same tool.

For a wider view, see our review of Locust load testing.

FAQ

Is Locust faster than k6? We have not measured this ourselves, so we will not name a winner. The fair test is the same scenario with both tools on your own hardware.

Can Locust run k6 scripts? Not according to the Locust docs, which describe tests as Python code in a locustfile. A k6 script is JavaScript, so it has to be rewritten as a Python user class, and the thresholds become a listener.

Can LoadFocus run Locust tests? No. LoadFocus runs k6 scripts and JMeter test plans. To scale a Locust test, use its master and worker mode, the Kubernetes operator or Azure Load Testing.

Related reading

• Locust load testing: a review of the Python tool
• Locust vs JMeter: Python scripts or JMeter test plans?
• Gatling vs k6: JVM simulations or a single Go binary?
• k6 vs Artillery: which load testing tool fits your team?
• Open vs closed workload model: which one should you use?
• Azure Load Testing: a review of Microsoft’s service

The technical claims in this article have not been independently reviewed.