Klevu vs Luigi's Box
One of fourteen models named Klevu first on the direct prompt; zero named Luigi's Box. Klevu was named by thirteen of the fourteen models and Luigi's Box by seven and Klevu carries 43 labels and Luigi's Box 11, so the shares are not directly comparable.
Named in one category this edition.
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 ecommerce search and merchandising page.
By framing
KlevuFirst choices, of fourteen modelsLuigi's Box
Across every category in the October 2026 Edition, Klevu and Luigi's Box were named in the same answer twenty times, of the 105 answers naming Klevu and the 37 naming Luigi's Box. In those answers Luigi's Box took the first choice zero times and Klevu 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 | | |
Klevu Luigi's Box first choice named as an alternative argued againstblank: not namedEach cell is one answer, Klevu on the left and Luigi's Box on the right.The direct prompt
Klevu first, Luigi's Box not the choice
1 of 14 modelsLuigi's Box was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
8 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
Klevu11%#3 of 13Luigi's Box0%#8 of 13Klevu0%#9 of 9Luigi's Box0%#– of 9What the models said about Klevu
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Klevu's G2 review sample is very small, so individual complaints—including one about renewal terms—aren't enough to establish a general pattern” GPT-6 Luna · negative prompt · soft negative
“Klevu has less robust analytics and recommendations compared to other tools... may not scale well or support large catalogs” Claude Haiku 4.5 · negative prompt · soft negative
“Limited advanced merchandising — Strong on search basics, but users note gaps in complex merchandising features.” DeepSeek V4 Flash · negative prompt · soft negative
“Often top for mid-market B2B/B2C hybrids... "Mid-market value champion" with 32% conversion lifts” Grok 4.1 Fast · direct prompt · first choice
“Klevu: Best AI-First Option for Modern B2B ... Klevu is the gold standard” Gemini 3.5 Flash · paraphrase prompt · first choice
“I recommend Klevu as the best onsite product search engine” Mistral Small · paraphrase prompt · first choice
What the models said about Luigi's Box
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“the best ecommerce search and merchandising platform for a company with a limited budget is Luigi's Box” Llama 4 Maverick · budget prompt · first choice
“High-rated alternatives like Algolia, Klevu, Clerk.io, Luigi's Box, or Fast Simon score well on G2” Grok 4.1 Fast · negative prompt · alternative
“Luigi's Box | Merchandising-led teams wanting strong relevance tuning” DeepSeek V4 Flash · scale prompt · alternative
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.