ActivTrak vs Hubstaff
Nine of fourteen models named ActivTrak first on the direct prompt; zero named Hubstaff. Both were named by all fourteen models and ActivTrak carries 51 labels and Hubstaff 44, so the shares are not directly comparable.
Named in three categories this edition.
Named in seven categories this edition.
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 employee monitoring page.
By framing
ActivTrakFirst choices, of fourteen modelsHubstaff
Across every category in the October 2026 Edition, ActivTrak and Hubstaff were named in the same answer 105 times, of the 151 answers naming ActivTrak and the 163 naming Hubstaff. In those answers Hubstaff took the first choice seventeen times and ActivTrak twenty-nine.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | |||
| GPT-5.4 mini | | | | |||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | | |||
| Grok 4.1 Fast | | | | | | |
| 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 | | | | | |
ActivTrak Hubstaff first choice named as an alternative argued againstblank: not namedEach cell is one answer, ActivTrak on the left and Hubstaff on the right.The direct prompt
ActivTrak first, Hubstaff an alternative
9 of 14 modelsHubstaff was named in the answer but not as the choice, or not at all.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.Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.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
Hubstaff23%#1 of 10ActivTrak15%#2 of 10ActivTrak33%#1 of 7Hubstaff8%#4 of 7What the models said about ActivTrak
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Screen monitoring, "bossware" classification in research” Kimi K2 · negative prompt · hard negative
“Some expensive tools (like ActivTrak) require a minimum purchase of 5 licenses (billed annually) even for the lowest tier.” GLM 4.7 FlashX · budget prompt · soft negative
“A commonly mentioned less intrusive alternative is ActivTrak, described as offering "real-time activity monitoring without keystroke logging..."” Muse Glimmer 30B · negative prompt · first choice
“Start with ActivTrak for the overall organization if you need to understand productivity trends, but avoid it for sales teams.” Qwen 3.7 Flash · direct prompt · first choice
“ActivTrak is the top recommendation due to its robust analytics, ease of use, and focus on actionable insights” Mistral Small · direct prompt · first choice
What the models said about Hubstaff
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Frequently cited in privacy complaints for requiring installation on work devices with tracking capabilities” GLM 4.7 FlashX · negative prompt · hard negative
“If your budget is tight, Hubstaff is probably the best starting point for most small and mid-sized companies.” GPT-5.4 mini · budget prompt · first choice
“If you want the best overall value on a limited budget, pick Hubstaff.” Perplexity Sonar · budget prompt · first choice
“### 1. Hubstaff - Best for: Time tracking and payroll integration” MiniMax M2.5 · comparative prompt · first choice
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.