will this be open weights?
This is something I would like to know as well.
But if not, does anybody know a recommended way to attach vision to deepseek flash (on a self-hosted infrastructure)?
DeepSeek-v4-flash-vision-exp
21–30 of 169 posts
Re: DeepSeek-v4-flash-vision-exp
#22Re: DeepSeek-v4-flash-vision-exp
#23I've heard that DeepSeek v4 Flash 0731 has frequently assumed that it has vision capabilities and then resorts to inventing text-based image analysis tools when it finds that it actually can't see. In that case, this is a great upgrade for the model. Anecdotally, I had to tell 0731 to refrain from viewing screenshots since it kept breaking its sessions by trying to read images.
It tried to recreate vision by analyzing pixels on 3 separate projects I had it working on.
Re: DeepSeek-v4-flash-vision-exp
#24800x800 is 640,000 pixels, or 0.64 Megapixels. That is less than the resolution of computer screens from 1995, Super VGA which has around 0.79 MPs. This is useful for a reasonable amount of use-cases, but I think the watershed rez will be around triple that, ~1080p, which is enough for almost anything, except small text and subtle details.
I typically provide small screenshots to llms so this seems fine for that usecase, providing an entire screens context seems cause confusion with a lot of llms.
Re: DeepSeek-v4-flash-vision-exp
#25Re: DeepSeek-v4-flash-vision-exp
#26Interesting. Wasn't Deepseek's founder saying that they had explicitly decided not to focus on multimodal models at all and were going text-only because they believed it was enough to achieve AGI?
I think you're thinking of Dario saying this about image generation.
Re: DeepSeek-v4-flash-vision-exp
#27will this be open weights?
This is something I would like to know as well. But if not, does anybody know a recommended way to attach vision to deepseek flash (on a self-hosted infrastructure)?
Generally you just add a vision model as an MCP server like this: https://github.com/DavidEasden/opencode-vision
Re: DeepSeek-v4-flash-vision-exp
#28Earlier quoted context omitted.
Can split and feed?
that's difficult as well, how do you k ow where to split?
There are models specifically for splitting an image into text regions, e.g. PP-DocLayoutV3 https://huggingface.co/PaddlePaddle/PP-DocLayoutV3
I am using a stripped-down minimal version of it which I uploaded here, since I am not a fan of huge dependency trees: https://github.com/99991/simple-pp-doclayoutv3
Another recent model for this task is Unlimited-OCR: https://github.com/baidu/Unlimited-OCR
Re: DeepSeek-v4-flash-vision-exp
#29Earlier quoted context omitted.
Oof 800 by 800 kills a lot of use cases
For most use cases you can fix that in the harness. Just give the model a tool to request a crop of specific coordinates of any image it has in its context. Call the tool "zoom" and it should be intuitive for the model Maybe there are some use cases where you need high detail everywhere at once, but for OCR of small text and the like a zoom ability should be sufficient
For really dumb models I've also had success automatically cropping it into a grid of N images with the max size, then processing each cell individually, then once all been processed, do one final call with resized image + all other context previously generated per cell. Basically a workaround to the image dimension restrictions without loosing fidelity. Works well with even dumb 7B models.
Can't remember if I stole this idea from some existing public harness though, can't remember. If someone knows of public harnesses that do this already, please share them :)
Re: DeepSeek-v4-flash-vision-exp
#30will this be open weights?
I believe so. Openness has always been a consistent tradition of DeepSeek