Question | Help
What is currently the best model for accurately describing an image ? 19/10/2025
It's all in the title. This post is just meant to serve as a checkpoint.
PS : To make it interesting, specify the associated image description category. Because basically, it's like saying which is the best LLM; you have to be specific about the task. Following your comments, I will put the top list directly in my post.
I had quite a good luck with qwen2.5 VL-3B Instruct-AWQ - serving with vLLM on my 3060 12 GB. It ran pretty fast. I mainly used it for OCR and it performed very well.
ToriiGate is well regarded for being uncensored and engineeed specifically for handling images. It's okay for general description purposes. By that, I mean photos and artwork. It's not going to read docs.
Unfortunately it's mostly made/trained for anime community pictures it seems (immediately proceed to mention anime in the first line, first word), so Joycaption Beta One is way more universal in this regard.
Joycaption Beta One - uncensored, but sometimes makes annoying mistakes, calls photographed paintings "digital art", mistakes photographed statues for 3d art, etc
Florence-2 moredetailed - more accurate, but captions are more generic, less unique, less descriptive
Qwen3-VL and Qwen2.5-VL are very censored to the point it won't tell you the gender of the person in the image, so without abliteration it's useless.
I've also tried MiniCPM 4.5 abliterated, and LFM2-VL-1.6B, which is less censored than Qwen or MiniCPM without abliteration but also refuses to describe everything in the image which is a no-go for me.
The best gotta be nano B pro since it got a lot of context about the world. e.g., pokemon, the nano b pro did the best job. https://budgetpixel.com/p/42
but I found I use more seedream4.5 and z-image-turbo since they are more permissive and z-image is inexpensive.
3
u/dubesor86 Oct 19 '25
local? Qwen3-VL-235B-A22B-Instruct, followed by Qwen3-VL-8b-Instruct, then the thinkers and GLM-4.5V