Data as of Aug 25, 2026 · Based on 1,707 AI responses · See how Parse measures this
API Testing and Load Testing Tools
Parse
https://parse.gl
Gatling has surged to the #1 rank for API and load testing tools, climbing from #15 since October 2025. This reflects a broader trend where AI models increasingly favor modern, developer-centric tools like k6 and over more traditional solutions.
| # | Brand | What AI says | Mention rate |
|---|---|---|---|
| 1 | 37% | ||
| 2 | 34% | ||
| 3 | A modern, developer-friendly choice, scripting load tests in JavaScript for CI/CD pipelines. | 34% | |
| 4 | Praised for high-performance, efficient load testing with its Scala-based DSL. | 34% | |
| 5 | A Python-based tool for scripting complex user behavior and distributed load tests. | 30% | |
| 6 | 27% | ||
| 7 | 22% | ||
| 8 | 18% | ||
| 9 | The leading choice for realistic API mocking, simulating latency and error states. | 18% | |
| 10 | Uses AI to generate realistic load by replaying production-like traffic patterns. | 17% | |
| 11 | Open-source tool for replaying real production HTTP traffic for realistic load profiles. | 15% | |
| 12 | 13% | ||
| 13 | 10% | ||
| 14 | 9% | ||
| 15 | 9% | ||
| 16 | 9% | ||
| 17 | 7% | ||
| 18 | 7% | ||
| 19 | 6% | ||
| 20 | 6% | ||
| 21 | 6% | ||
| 22 | 5% | ||
| 23 | 5% | ||
| 24 | 4% | ||
| 25 | 4% |
Who wins on each AI
The same market, seen by two models.
Sources AI cited
pflb.us is the page AI reaches for most here, cited in 47% of analyzed answers.
Climbed from 7% citation in Oct 2025 to 44% in Mar 2026.
Moved from 9% citation in Oct 2025 to 49% in Mar 2026.
Dropped from rank #2 in Oct 2025 to #13 in Mar 2026.
“A load-testing ecosystem with recently added AI features for assistance and data generation.” → “A comprehensive platform that integrates AI to analyze production data and generate realistic scenarios.”
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
| 47% | 44% | ||
| 43% | 40% | ||
| 44% | 27% | ||
| 0% | 40% | ||
| 37% | 36% |
The two models disagree most about Tricentis NeoLoad (ChatGPT #15, Google #4) and OpenText LoadRunner Enterprise (ChatGPT #13, Google #20).
Gatling has surged to the #1 rank for API and load testing tools, climbing from #15 since October 2025. This reflects a broader trend where AI models increasingly favor modern, developer-centric tools like k6 and Locust over more traditional solutions.
Across 1,707 AI responses, Apache Software Foundation is mentioned most, named in 37% of them, followed by Perforce (34%) and k6 (34%).
Parse measures each brand's mention rate — the share of answers naming it — across 1,707 AI responses to this market's buyer questions. Answers are collected daily and the ranking is published weekly.
Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.
Initially, AI assistants recommended enterprise tools like BlazeMeter and
Tricentis NeoLoad. Since November 2025,
PFLB has been consistently cited for its specific feature of replaying production traffic patterns, while
GoReplay is also frequently mentioned as an open-source alternative.
Initially, AI assistants recommended enterprise tools like BlazeMeter and
Tricentis NeoLoad. Since November 2025,
PFLB has been consistently cited for its specific feature of replaying production traffic patterns, while is also frequently mentioned as an open-source alternative.
Responses consistently recommend a mix of enterprise platforms like OpenText LoadRunner and scalable open-source tools. is frequently highlighted for its ability to simulate millions of users in distributed mode, with and k6 also cited for their efficiency at scale.
Brands mentioned
Brands mentioned
I am looking for a load testing tool that can simulate millions of concurrent users.
Responses consistently recommend a mix of enterprise platforms like OpenText LoadRunner and scalable open-source tools.
Locust is frequently highlighted for its ability to simulate millions of users in distributed mode, with
Gatling and k6 also cited for their efficiency at scale.
The market map
Recommended by need