Earlier quoted context omitted.
One possibility. Certain countries will always be able to produce open models cheaper than others. USA and Europe probably won't be able. However, due to national security and wanting to promote their models overseas instead of letting their competitors promote theirs, the governments of USA and Europe will subsidize models which will lead their competitors to (further?) subsidies. There is a promotional aspect as we…
What's your take on why certain countries will have it cheaper and subsidies being at the forefront? An energy driven race to the bottom, is perhaps what you mean? I would suppose I have been seeing that China is ahead on their Renewables plan compared to the rest of the world, and they still have the lead on coal energy, so they'd likely be the winners on that front. But did you actually mean something else?
Qwen2.5-VL-32B: Smarter and Lighter
231–240 of 303 posts
Re: Qwen2.5-VL-32B: Smarter and Lighter
#232Earlier quoted context omitted.
Since we are on HN here, I can highly recommend open-webui with some OpenAI-compatible provider. I'm running with Deep Infra for more than a year now and am very happy. New models are usually available within one or two days after release. Also have some friends who use the service almost daily.
I'm using open-webui at home with a couple of different models. gemma2-9b fits in VRAM on a NV 3060 card + performs nicely.
Do you have rough indication of token/s ?
Re: Qwen2.5-VL-32B: Smarter and Lighter
#233Earlier quoted context omitted.
it seems that this free version "may use your prompts and completions to train new models" https://openrouter.ai/deepseek/deepseek-chat-v3-0324:free do you think this needs attention?
Since we are on HN here, I can highly recommend open-webui with some OpenAI-compatible provider. I'm running with Deep Infra for more than a year now and am very happy. New models are usually available within one or two days after release. Also have some friends who use the service almost daily.
Re: Qwen2.5-VL-32B: Smarter and Lighter
#234Re: Qwen2.5-VL-32B: Smarter and Lighter
#235Earlier quoted context omitted.
I tried R1 through Kagi and it’s similarly censored. Even the distill of llama running on Groq is censored.
Kagi may be using the official DeepSeek API and not hosting the model itself. There is work being done to make it completely uncensored: https://github.com/huggingface/open-r1 https://ollama.com/huihui_ai/deepseek-r1-abliterated I was mistaken though, it is more than just a system prompt causing the censorship.
Re: Qwen2.5-VL-32B: Smarter and Lighter
#236This model is available for MLX now, in various different sizes. I ran https://huggingface.co/mlx-community/Qwen2.5-VL-32B-Instruct... using uv (so no need to install libraries first) and https://github.com/Blaizzy/mlx-vlm like this: uv run --with 'numpy That downloaded an ~18GB model and gave me a VERY impressive result, shown at the bottom here: https://simonwillison.net/2025/Mar/24/qwen25-vl-32b/
Is UV the best way to run it?
Re: Qwen2.5-VL-32B: Smarter and Lighter
#237We were using Llama vision 3.2 a few months back and were very frustrated with it (both in term of speed and results quality). Some day we were looking for alternatives on Hugging Face and eventually stumbled upon Qwen. The difference in accuracy and speed absolutely blew our mind. We ask it to find something in an image and we get a response in like half a second with a 4090 and it's most of the time correct. What's…
Re: Qwen2.5-VL-32B: Smarter and Lighter
#238Earlier quoted context omitted.
Oh, I have a question, maybe you know. Assuming the same model sizes in gigabytes, which one to choose: a higher-B lower-bit or a lower-B higher-bit? Is there a silver bullet? Like “yeah always take 4-bit 13B over 8-bit 7B”. Or are same-sized models basically equal in this regard?
I would say 9 times out of 10, you will get better results from a Q4 model that’s a size class larger than a smaller model at Q8. But it’s best not to go below Q4.
Re: Qwen2.5-VL-32B: Smarter and Lighter
#239We were using Llama vision 3.2 a few months back and were very frustrated with it (both in term of speed and results quality). Some day we were looking for alternatives on Hugging Face and eventually stumbled upon Qwen. The difference in accuracy and speed absolutely blew our mind. We ask it to find something in an image and we get a response in like half a second with a 4090 and it's most of the time correct. What's…
Re: Qwen2.5-VL-32B: Smarter and Lighter
#240Any security risks running these Chinese LLMs on my local computer?
https://news.ycombinator.com/item?id=43121383
It would have to be from unsupervised tool usage or accepting backdoored code, not traditional remote execution from merely inferencing the weights.