Ten of fourteen models named Google Tag Manager first on the direct prompt; one named Tealium iQ Tag Management. Both were named by all fourteen models and Google Tag Manager carries 85 labels and Tealium iQ Tag Management 57, so the shares are not directly comparable.
By Google, Mountain View, California, United States, founded 1998. Named in two categories this edition.
By Tealium, San Diego, United States, founded 2008. Named in one category 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 tag management page.
Across every category in the October 2026 Edition, Google Tag Manager and Tealium iQ Tag Management were named in the same answer 174 times, of the 228 answers naming Google Tag Manager and the 183 naming Tealium iQ Tag Management. In those answers Tealium iQ Tag Management took the first choice thirty-eight times and Google Tag Manager 102.
| 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 |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid paid enterprise suites like GTM 360 unless you have a clear need for enterprise governance features” GPT-5.4 mini · budget prompt · hard negative
“basic free tools like Google Tag Manager (GTM), which may suffice for smaller setups but often lacks robust permissions and support for larger teams” Grok 4.1 Fast · scale prompt · soft negative
“Free version lacks enterprise RBAC, SLAs (GTM AI Index: 32% negative).<br>- Unreliable preview/debugger; slowdowns; security via custom HTML” Grok 4.1 Fast · negative prompt · soft negative
“Google Tag Manager is the most common general-purpose choice because it is free, simple to implement, and integrates well with Google products.” Perplexity Sonar · comparative prompt · first choice
“The best tag management system for a company with a limited budget is Google Tag Manager. It is free and has a broad template ecosystem” Llama 4 Maverick · budget prompt · first choice
“the most widely recommended solution for mid-market businesses due to its ease of use, robust features, and cost-effectiveness” Mistral Small · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Enterprise Platforms to Avoid (For Mid-Market) ... like Tealium iQ ... you should probably steer clear” Gemini 3.5 Flash · direct prompt · hard negative
“noted for unpredictable costs and is listed among systems to avoid for budget predictability” Mistral Small · negative prompt · hard negative
“When to Avoid: Tealium and Adobe ... likely overkill and too expensive” GLM 4.7 FlashX · paraphrase prompt · hard negative
“Strongest enterprise governance, privacy, and server-side capabilities. Best if compliance/security is a priority. More expensive and complex.” DeepSeek V4 Flash · scale prompt · first choice
“Shortlist 3–5 vendors: Start with GTM/GTM 360 (free trial), Tealium, Adobe.... Tealium (enterprise governance)” Grok 4.1 Fast · scale prompt · first choice
“Tealium iQ is the category standard for mid-market companies that outgrow GTM” Kimi K2 · scale 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.