# Locust vs k6

> Locust is a Python, code-defined load framework with a simple distributed model. k6 is a JavaScript-focused tool with polished CLI metrics and cloud options. Python shops often prefer Locust; polyglot or JS teams often prefer k6.

- Canonical: https://perf.jmeter.ai/vs/locust-vs-grafana-k6/
- Compared: [Locust](https://perf.jmeter.ai/tools/locust/) · [Grafana k6](https://perf.jmeter.ai/tools/grafana-k6/)

## Verdict
Locust is approachable for Python engineers who want user-behavior scripts and easy horizontal workers. k6 offers a more opinionated developer UX, checks/thresholds, and a commercial cloud line under Grafana. Neither replaces multi-protocol enterprise suites by itself.

## Specs
| Field | Locust | k6 |
| --- | --- | --- |
| Vendor | Locust authors | Grafana Labs |
| Category | Load Testing | Load Testing |
| License | Open Source | Open Source |
| Deployment | Self-hosted | Self-hosted |
| Status | Active | Active |
| First released | 2011 | 2017 |
| Pricing | Free; MIT License. | Free; AGPL-3.0 license. |
| Scripting | Python | JavaScript, TypeScript |
| Protocols | HTTP, HTTPS, WebSocket | HTTP, HTTPS, WebSocket, gRPC |
| OS support | Windows, macOS, Linux | Windows, macOS, Linux |

## How to choose
- Choose Locust when Python is the team language and you want flexible user tasks.
- Choose k6 for JS scenarios, thresholds, and Grafana-aligned reporting.
- Both are open source and self-hostable; k6 has a clearer SaaS upsell path.
- For pure micro-benchmarks, also evaluate wrk, hey, or vegeta.

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Curated by NaveenKumar Namachivayam (QAInsights) · methodology: https://perf.jmeter.ai/about/#methodology · corrections: https://github.com/QAInsights/Performance-Testing-Tools/issues/new?title=Tool%20submission%3A%20&body=Tool%20name%3A%20%0AOfficial%20URL%3A%20%0AWhat%20should%20be%20added%20or%20corrected%3F%20%0A