Excel-based / Legacy
–Too few to rank
1/14Models named it
0First choices
1Warnings
November 2026 Edition · all company sizes counted.
What AI models recommend
Named, too few times to rank.
A product needs 10 labels in a category before a share is stated. Excel-based / Legacy has 1.
Why models recommend it
No positive label carried a quote.
What gives them pause
“Tier 3 (Excel-based / Legacy): Generally avoid these at the 500-headcount mark due to security risks and lack of collaboration.”Qwen 3.7 Flash · Scale-constrained question · warning
Also on the shortlist
The products named in the same answers as Excel-based / Legacy, over the 1 answer that named it, and how often each was the first choice instead.
A side-by-side page exists where both products are among a category's top eight.
How this is measured
Fourteen AI models from 12 labs are asked the same buying questions six ways, for three company sizes. Standings refresh every edition.
Gane sells AI visibility software. No company can pay to change a result.
Read the method →By model
How each model answered on Excel-based / Legacy across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
| Model | First choice | Alternative | Mention | Warning | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 1 | 1 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |