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GPT 5.6 Sol is the best "vision" model OpenAI ever released
81–90 of 194 posts
Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#82I'm a little bit disappointed that vision seems to fall before language at scale.
It seems pretty counter intuitive that we can't do vision significantly better with specialized techniques.
Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#83I really like the combo 5.6 Luna & Sol for price and performance and would be perfectly happy if they stayed here for a moment without mucking about with sidegrades that I think AI evolution has often felt like lately.
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Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#84The summary "There are still clear limits. Gemini 3.5 Flash remains a better practical choice [than GPT 5.6 Sol] for high-volume detection and counting in our benchmark, especially at its price." seems rather understated ! GPT 5.6 Sol was outperformed on all benchmarks by Gemini 3.5 Flash, apart from a single exception (OCR) where Fable was the winner. Gemini 3.5 Flash not only outperformed GPT 5.6 Sol, but did so at…
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Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#85Ironically, the pill counting example selected to showcase "the best vision model" can be easily solved with OpenCV template matching, a technology created 25 years ago.
I'm assuming you mean that this tech became available in OpenCV 25 years ago, but as it turns out, the underlying tech can be traced back much further, at least as far as 1977! :) https://ieeexplore.ieee.org/document/1674847 G. J. Vanderbrug and A. Rosenfeld, “Two-Stage Template Matching,” IEEE Transactions on Computers, Vol. C-26, No. 4, pp. 384–393, April 1977. DOI: 10.1109/TC.1977.1674847
Exactly my point. Template rotation is a trivial operation as well.
Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#86Earlier quoted context omitted.
Gemini is still my top choice within production software for typical data extraction from unstructured data. Gemini Flash Lite feels like a cheat code for speed, and it's really cheap. Some other Chinese models are also fast and cheap, but a harder sell in a U.S. production environment.
Yeah Gemini 3.5 Flash Lite is really good. Which Chinese models can you recommend?
I've been using Qwen3.5-9B, hosted locally for PDF data extraction and it performs pretty well when extracting data from tables and infographics
Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#87The summary "There are still clear limits. Gemini 3.5 Flash remains a better practical choice [than GPT 5.6 Sol] for high-volume detection and counting in our benchmark, especially at its price." seems rather understated ! GPT 5.6 Sol was outperformed on all benchmarks by Gemini 3.5 Flash, apart from a single exception (OCR) where Fable was the winner. Gemini 3.5 Flash not only outperformed GPT 5.6 Sol, but did so at…
Hi, I’m the author of this blog post. I wrote it about 4 weeks ago, and the VLM world is moving so fast that it’s already kinda outdated. I think Gemini 3.7 Flash might be a better choice now, especially when you factor in the price.
Here’s a comparison of the best low-cost models I put together last week. What’s crazy is that Gemini 3.7 Flash is now 50% off on OpenRouter, and this chart doesn’t even account for that discount. https://x.com/skalskip92/status/2088032652301304121?s=20
Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#88Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#89Does any popular NVR make a good use of LLMs (especially local models) getting decent at vision?
I've been using Reolink for years and been very satisfied with it.
The only quip is the default UI isn't very good. When changing that reaches the top of my priority list, I'll switch it since they don't force you into a walled garden. Plan is to run it through frigate into HomeAssistant and use a UI from them. I've never used frigate before though so it'll be a learning process if plug and play solutions aren't already available
Re: GPT 5.6 Sol is the best "vision" model OpenAI ever released
#90Ironically, the pill counting example selected to showcase "the best vision model" can be easily solved with OpenCV template matching, a technology created 25 years ago.
Basic Template matching has severe limitations around scaling, rotation, and perspective. In my experience it greatly underperforms compared to deep network object detectors. My experience- and I imagine others have different experiences- is that SIFT techniques also fail pretty badly with noisy data.
That's correct, and I was specifically referring to the example chosen - where scale and perspective are known. Template rotation is relatively easy as well - but partial obstructions would pose a problem.
Another application where template matching would work brilliantly? Car counting in parking lots using satellite imagery.
Source: I did this [1] using OpenCV and template matching. Outperformed "Cars Overhead with Context" models.
https://abcnews.com/International/satellite-data-suggests-co...