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Website and synthetic monitoring · November 2026 Edition

Checkly vs Uptime Kuma

Zero of fourteen models named Checkly first on the direct prompt; zero named Uptime Kuma. Checkly was named by eleven of the fourteen models and Uptime Kuma by twelve and Checkly carries 27 labels and Uptime Kuma 17, so the shares are not directly comparable.

Checkly

accepted challenger

Named in one category this edition.

Uptime Kuma

accepted challenger

Named in five categories this edition.

First-choice share6%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#7A position in a field of 11; printed, not drawn.
Labels2717A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Checkly reading right to left. Rank and label count are printed, not drawn.Better Stack was named alongside these two in twelve of the fourteen direct answers. UptimeRobot vs Checkly · UptimeRobot vs Uptime Kuma · Better Stack vs Checkly

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the website and synthetic monitoring page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
ChecklyFirst choices, of fourteen modelsUptime Kuma
Direct00
Paraphrase30
Comparative00
Budget-constrained02
Scale-constrained00
Negative00
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the November 2026 Edition, Checkly and Uptime Kuma were named in the same answer nine times, of the 55 answers naming Checkly and the 54 naming Uptime Kuma. In those answers Uptime Kuma took the first choice one time and Checkly zero.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Checkly and Uptime Kuma stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
Checkly Uptime Kuma first choice named as an alternative argued againstblank: not namedEach cell is one answer, Checkly on the left and Uptime Kuma on the right.

The direct prompt

The plain question, one answer per model, grouped by where Checkly and Uptime Kuma stood in it.

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashBetter Stack alternatives: Checkly, Datadog Synthetic Monitoring, StatusCake
Perplexity SonarBetter Stack alternatives: Checkly, Uptime.com, UptimeRobot
Llama 4 MaverickUptimeRobot alternatives: Better Stack, Checkly, Paessler PRTG, Pingdom
GPT-6 LunaBetter Stack alternatives: Checkly, Datadog Synthetic Monitoring

Neither was named

10 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Pingdom alternatives: Atlassian, Datadog Synthetic Monitoring, New Relic Synthetics, Statuspage, UptimeRobot
GPT-5.4 miniPingdom alternatives: Datadog Synthetic Monitoring, Site24x7, UptimeRobot
Grok 4.20UptimeRobot alternatives: Better Stack, Site24x7
Mistral SmallUptimeRobot alternatives: Better Stack
DeepSeek V4 FlashBetter Stack alternatives: Uptime.com, UptimeRobot
Qwen 3.7 FlashUptimeRobot alternatives: Better Stack, Pingdom
Kimi K2StatusCake alternatives: Better Stack, Uptime.com
GLM 4.7 FlashXUptimeRobot alternatives: Better Stack, Hyperping
MiniMax M2.5Better Stack, Site24x7 alternatives: Datadog Synthetic Monitoring
Muse Glimmer 30BBetter Stack, Hyperping alternatives: Datadog Synthetic Monitoring, Pingdom, Site24x7, UptimeRobot

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Uptime Kuma leads by four points.
Uptime Kuma4%#5 of 12
Checkly0%#11 of 12
The full small business standing →
Mid-marketThe figures above
The order flips: Checkly leads at mid-market.
Checkly6%#4 of 11
Uptime Kuma4%#7 of 11
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Checkly0%#12 of 14
Uptime Kuma0%#– of 14
The full enterprise standing →

What the models said about Checkly

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Start with Site24x7 or Checkly depending on whether you prefer GUI-based or code-first setup.” Kimi K2 · paraphrase prompt · first choice
“Checkly or Grafana Cloud Synthetic Monitoring gives you the best cost-to-coverage ratio” Muse Glimmer 30B · paraphrase prompt · first choice
“Best Overall for Modern Tech Teams: Checkly” Gemini 3.5 Flash · paraphrase prompt · first choice

What the models said about Uptime Kuma

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“If you have a technical person on staff: Go with Uptime Kuma on a free VPS. It gives you enterprise-level monitoring at $0/month.” Kimi K2 · budget prompt · first choice
“Uptime Kuma (Best Overall Value / Self-Hosted) ... 100% Free & Open-Source” Gemini 3.5 Flash · budget prompt · first choice
“Uptime Kuma is the cheapest option because it's free/open-source; the tradeoff is that you have to run and maintain it yourself” GPT-5.4 mini · budget prompt · alternative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.