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Posted by plurby 1 day ago

GPT 5.6 Sol is the best "vision" model OpenAI ever released(blog.roboflow.com)
341 points | 162 commentspage 2
schopra909 21 hours ago|
From our experiments it’s the best video captioning model in the world by a mile. This was not the case a year ago.

When reasoning got introduced a year ago to GPT 5, on average the model performed worse than GPT4-o for short video clip captioning (Ie hallucinating actions that didn’t happen). The old GPT 5 was extremely finicky in terms of fps sample rate.

The other SOTA LLMs (like Gemini Pro) have clearly been optimized for long video understanding, since they can’t see almost anything sub-second (even if you up the frame sampling rate).

Sol is the first model we’ve seen to accurately caption complex sub-second movements (eg woman suddenly turns heard head to right). It’s robust to different fps sample rates so I can only guess that they trained on videos sampled at different fps.

Vacyyyy 5 hours ago|
Have you checked versus more recent Gemini models like 3.5 or perhaps 3.7?
faxmeyourcode 21 hours ago||
It's not clear to me from the article, are they asking sol to output bounding box coordinates with some kind of structured outputs?

Anecdotal but I've seen it use python to crop, zoom, and "enhance" (fiddle with sharpness and brightness) images to read sections of handwritten census data from the 1800s. Feels like that there might just be a mismatch of capabilities when it comes to straight outputting coordinates but I bet the model is better at actually finding the answer given any tools available. Which I get is a bit of an apples and oranges situation.

I've also tried to use it to identify an old pair of glasses and it didn't stand a chance, so I do think it's not quite there yet when it comes to some vision tasks.

lwarfield 20 hours ago||
I currently have fable organize a bunch of 5.6 sol agents when working on my personal projects. This makes me wonder if I should add something along the lines of "For tasks that involve visual analysis, have gemini 3.7 look at images generated."

Overall I've been hooked on using agents from different companies for what they are best at (Thanks to Theo). Fable is expensive, but unmatched for planning and top level organization of other agents. Sol is fast, will persistantly go after goals (sometimes to its detriment), and does well with computer use.

ALLTaken 21 hours ago||
I actually favor Qwen3.8 and run it locally + use the Token-Plan on AlibabaCloud, when I need faster results. Kind of favor it over GPT5.6 Sol.

Also it seems to be more capable, need to test more, but I think it's at least getting on par and it's fully open-source and open-weights.

Here's some benchmarks:

https://benchlm.ai/compare/gpt-5-6-sol-vs-qwen3-8-max

https://qwen.ai/blog?id=qwen3.8#full-benchmark-table (incredible UI/UX demos)

https://venturebeat.com/technology/qwen3-8-max-arrives-with-...

EDIT: Am I early to the discussion, or is none else using Qwen3.8-max?

barrenko 16 hours ago||
I thought Qwen 3.8 max doesn't have vision?
ALLTaken 18 hours ago||
huh, why am I being shadow banned?

Does YC have similar problems like those at wikipedia/reddit? (wikipedia-editor-wars, or reddit-mod-wars)

HDBaseT 11 hours ago||
You aren't being "shadow banned".

I concur with your conclusion, Qwen 3.8 has exceptional Vision Capabilities. The other commenter mentioned "I thought Qwen 3.8 didn't have Vision", it does, just not on the open weights version, only via official API.

iamniels 22 hours ago||
I understand why you would like to use an LLM for vision. I do it myself often enough. I don't understand however, why the pill detection and counting is included in this benchmark. That is a task which you would perform with OpenCV right?

In my personal mini benchmark minicpm-v-4.6 scores amazingly well. Its a 0.8B model which runs fine on many consumer hardware.

throwup238 22 hours ago||
Generating datasets to train more efficient models is a common use case for VLMs, especially frontier ones. It makes it much cheaper to create that initial dataset and you can abuse the nondeterminism of LLMs to identify data for human review (if they don’t converge, escalate to a human).
rhplus 22 hours ago|||
Especially the pill counting example. The best model was shown at 81.1% accuracy, which is a terrible rate for pharmacy scenarios. It seems like implementors would be better off instructing the models to use deterministic tools (like OpenCV) until the models are at 99.99% accuracy (or whatever an acceptable error rate is for pharmacy techs).
jacquesm 21 hours ago||
I think that is because people perceive OpenCV as 'hard to use' and LLMs as easy to use.
TeMPOraL 17 hours ago||
OpenCV is no longer hard to use, it just takes longer. Still, a little more complicated than asking LLM to count.

To use an LLM, you just prompt it with an image + text saying "count the pills in this image".

To use OpenCV, ... you just prompt an LLM with an image + text saying "count the pills in this image, using OpenCV instead of eyeballing it".

(I like to throw in "produce intermediary artifacts so I can see the process" for more difficult tasks; this helps the model avoiding making hallucination-prone leaps and gives more opportunities to self-correct. At a cost of extra time and tokens, of course.)

Using OpenCV without an LLM? Nah, not touching that, I don't have free weekends to waste anymore.

jacquesm 15 hours ago||
I no longer use it but never felt it was particularly complicated, but since the days of resnet there are much faster ways to the goal.
kherud 22 hours ago||
So far I haven't seen a single model succeeding at transcribing sheet music, but I just tested it again with 5.6 Sol and it nailed the small test case. Fluently reading music requires multiple years of training for most people, but I feel like accurately following the horizontal lines trips up vision models in particular.
adrianh 20 hours ago|
For a bespoke model that transcribes sheet music images well, check out our system at Soundslice: https://www.soundslice.com/sheet-music-scanner/

It's not an LLM, it's a custom thing we built. Here's a comprehensive list of support for various notation glyphs: https://www.soundslice.com/help/en/creating/pdf-import/294/s...

sscaryterry 23 hours ago||
My anecdotal evidence says its still as blind as any other model, it has no taste, no attention to any sort of detail.
howdareme 23 hours ago|
How can a vision model have taste?
sarreph 23 hours ago|||
If you're doing any kind of inference that is multi-modal and non-factual, opinions and biases will affect any kind of assessment of a visual that you provide to a model.

For example, a UI / UX professional being asked to appraise a website screenshot may determine that the image in question has "desirable" traits which are inherently not deterministically measurable. Such as, if the interface elements have strong information hierarchy, or if they are deemed to be "fashionable" with current UI trends.

DaiPlusPlus 23 hours ago||
> if the interface elements have strong information hierarchy

...but that's an example of a UX/usability matter that can be assessed objectively and non-subjectively.

sarreph 21 hours ago||
I disagree.

Is 16 px or 14 px a better font-size value for a subheading, in a hypothetical layout? Immediately that kind of decision, where both options are objectively good for 12 px paragraph text, suddenly becomes an issue of taste that cannot be evaluated crudely by an algorithm.

sscaryterry 23 hours ago|||
Replace taste with consistent if that helps you. Can it follow a design system...
yreg 23 hours ago|||
As a design system engineer I usually have to fight against the taste of the designers. (And I consider it natural.)

But, if you have a proper well documented design system and you tell the LLM to use the DS and to avoid styling hacks they can generally do it. Even the dumber ones than Sol 5.6.

Of course only if the design is achievable in the design system.

sscaryterry 23 hours ago||
This is not my experience at all.
velcrovan 23 hours ago|||
So, formulaic output…the opposite of taste
sscaryterry 23 hours ago||
Not really. Compliance with the letter of the law doesn't mean the intent is complied with.
chasd00 22 hours ago||
One of my friends (and BIL) own an architecture firm. They use AI to generate and quickly update renderings but they run into the equivalent of the 6 fingered hand problem. I sent him this article I wonder if the updated models can catch and fix mistakes made by previous models.
Mashimo 22 hours ago|
This article is about vision, not image output.
stavros 21 hours ago|||
Hence the "catch and fix mistakes" part.
bob1029 22 hours ago||
I've decided it's "good enough" after I saw it properly quote a string of text that was very roughly highlighted within a nested visual context. It also identified the context correctly (modal inside webapp inside screenshot of user desktop).
dostick 4 hours ago|
I wonder what about UI review, which model is the best?
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