SinoSend
Named, too few times to rank.
A product needs 10 labels in a category before a share is stated. SinoSend has 3.
Why models recommend it
“The best managed file transfer solution for a mid-market B2B company is SinoSend”Llama 4 Maverick · Direct question · first choice
“Best for Mid-Market: SinoSend”Muse Glimmer 30B · Direct question · alternative
What gives them pause
No model argued against it.
Also on the shortlist
The products named in the same answers as SinoSend, over the 5 answers that named it, and how often each was the first choice instead.
| Product | Named together | Picked instead | |
|---|---|---|---|
| 4 | 0 | View → | |
| 3 | 2 | View → | |
| 3 | 0 | View → | |
| 2 | 1 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → | |
| 2 | 0 | View → |
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 →Sources returned with these answers
Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted. These counts come from 5 of the 5 answers that named SinoSend and are not a share of its labels.
Domains cited
Twenty-eight of the twenty-eight domain citations in answers naming SinoSend came from a third party's page.
Pages cited
Pages are listed as the models cited them.
By model
| 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 | 1 | 0 | 0 | 0 | 1 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 1 | 0 | 1 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 1 | 0 | 0 | 1 |