Visier vs ChartHop
Three of twelve models named Visier first on the direct prompt; two named ChartHop. Visier was named by twelve of the twelve models and ChartHop by nine and Visier carries 48 labels and ChartHop 29, so the shares are not directly comparable.
Named in eight 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 twelve 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 people analytics page.
By framing
VisierFirst choices, of twelve modelsChartHop
Across every category in the September 2026 Edition, Visier and ChartHop were named in the same answer 118 times, of the 255 answers naming Visier and the 341 naming ChartHop. In those answers ChartHop took the first choice twelve times and Visier twenty-seven.
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 | | |
Visier ChartHop first choice named as an alternative argued againstblank: not namedEach cell is one answer, Visier on the left and ChartHop on the right.The direct prompt
Visier first, ChartHop an alternative
3 of 12 modelsChartHop was named in the answer but not as the choice, or not at all.ChartHop first, Visier not the choice
2 of 12 modelsVisier was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
5 of 12 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
2 of 12 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
Visier11%#4 of 12ChartHop8%#5 of 12What the models said about Visier
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Enterprise platforms like Visier offer custom enterprise pricing and implementation complexity that make them a poor fit for small to mid-market organizations.” Claude Haiku 4.5 · direct prompt · hard negative
“Platforms to Avoid in the Mid-Market ... Visier or One Model ... generally poor fits for the mid-market” Gemini 3.5 Flash · direct prompt · hard negative
“Avoid enterprise tools. Visier, Workday, and Eightfold AI typically require 500\u20131,000+ employees” DeepSeek V4 Flash · budget prompt · hard negative
“The category standard. Pre-built people-data model, deep metric library, 30M+ employee benchmarks, strong forecasting. Very powerful but complex.” Kimi K2 · comparative prompt · first choice
“| 1 | Visier | Large enterprises with complex, multi‑source workforce data | Deep workforce analytics, AI‑powered insights” GLM 4.7 FlashX · comparative prompt · first choice
“Market leader in people analytics, known for workforce planning, talent acquisition, and employee engagement.” Mistral Small · comparative prompt · first choice
What the models said about ChartHop
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“avoid it if your main goal is engagement analytics, sentiment analysis, or performance management” Perplexity Sonar · negative prompt · hard negative
“*Warning:* While the entry cost is low, ChartHop is highly modular... which can quickly drive up the price.” Gemini 3.5 Flash · budget prompt · soft negative
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.