Metricool vs Agorapulse
Zero of fourteen models named Metricool first on the direct prompt; one named Agorapulse. Metricool was named by ten of the fourteen models and Agorapulse by fourteen and Metricool carries 18 labels and Agorapulse 39, so the shares are not directly comparable.
Spain. Named in two categories this edition.
Named in two 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 social media management page.
By framing
MetricoolFirst choices, of fourteen modelsAgorapulse
Across every category in the October 2026 Edition, Metricool and Agorapulse were named in the same answer fourteen times, of the 44 answers naming Metricool and the 85 naming Agorapulse. In those answers Agorapulse took the first choice two times and Metricool two.
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 | | | |
Metricool Agorapulse first choice named as an alternative argued againstblank: not namedEach cell is one answer, Metricool on the left and Agorapulse on the right.The direct prompt
Agorapulse first, Metricool not the choice
1 of 14 modelsMetricool was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
7 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
6 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
Agorapulse6%#4 of 12Metricool4%#6 of 12Metricool8%#4 of 11Agorapulse6%#5 of 11Metricool0%#– of 9Agorapulse0%#8 of 9What the models said about Metricool
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Reddit mentions of "dubious practices" like astroturfing (fake reviews) and hacking concerns” Grok 4.1 Fast · negative prompt · hard negative
“For most small companies just starting out, Buffer or Metricool provide the best combination of ease-of-use, essential features, and low cost.” Qwen 3.7 Flash · budget prompt · first choice
“Go with Metricool if you want the best possible free option with great analytical reports.” Gemini 3.5 Flash · budget prompt · first choice
“For simple, budget-friendly scheduling: Look at Buffer, Metricool, or Publer.” Gemini 3.5 Flash · negative prompt · first choice
What the models said about Agorapulse
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Minor concerns: Occasional reports of slow or unhelpful customer support” Qwen 3.7 Flash · negative prompt · soft negative
“$79/user/month (annual) | Engagement-focused (less budget-friendly)” Grok 4.1 Fast · budget prompt · soft negative
“platforms like Agorapulse, Sendible, or later-stage reviews of Sprout Social tend to have fewer issues” GLM 4.7 FlashX · negative prompt · first choice
“Safer alternatives: Tools like Agorapulse or Sprout Social often rank higher for support and reliability” Grok 4.1 Fast · negative prompt · first choice
“My default recommendation: Agorapulse Professional for a mid-sized B2B team” GPT-6 Luna · paraphrase 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.