So today is Qwen. Tomorrow a new SOTA model from Google apparently, R2 next week.
We haven't hit the wall yet.
Qwen2.5-VL-32B: Smarter and Lighter
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Re: Qwen2.5-VL-32B: Smarter and Lighter
#12Big day for open source Chinese model releases - DeepSeek-v3-0324 came out today too, an updated version of DeepSeek v3 now under an MIT license (previously it was a custom DeepSeek license). https://simonwillison.net/2025/Mar/24/deepseek/
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?
That's typical of the free options on OpenRouter, if you don't want your inputs used for training you use the paid one: https://openrouter.ai/deepseek/deepseek-chat-v3-0324
Re: Qwen2.5-VL-32B: Smarter and Lighter
#1332B is one of my favourite model sizes at this point - large enough to be extremely capable (generally equivalent to GPT-4 March 2023 level performance, which is when LLMs first got really useful) but small enough you can run them on a single GPU or a reasonably well specced Mac laptop (32GB or more).
I don't think these models are GPT-4 level. Yes they seem to be on benchmarks, but it has been known that models increasingly use A/B testing in dataset curation and synthesis(using GPT 4 level models) to optimize not just the benchmarks but things which could be benchmarked like academics.
Re: Qwen2.5-VL-32B: Smarter and Lighter
#14Does anyone know how making the models multimodal impacts their text capabilities? The article is claiming this achieves good performance on pure text as well, but I'm curious if there is any analysis on how much impact it usually has.
I've seen some people claim it should make the models better at text, but I find that a little difficult to believe without data.
Re: Qwen2.5-VL-32B: Smarter and Lighter
#15To clarify: Qwen is made by Alibaba Cloud.
(It's not mentioned anywhere in the blog post.)
Re: Qwen2.5-VL-32B: Smarter and Lighter
#16Big day for open source Chinese model releases - DeepSeek-v3-0324 came out today too, an updated version of DeepSeek v3 now under an MIT license (previously it was a custom DeepSeek license). https://simonwillison.net/2025/Mar/24/deepseek/
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?
[deleted]
Re: Qwen2.5-VL-32B: Smarter and Lighter
#17Big day for open source Chinese model releases - DeepSeek-v3-0324 came out today too, an updated version of DeepSeek v3 now under an MIT license (previously it was a custom DeepSeek license). https://simonwillison.net/2025/Mar/24/deepseek/
Pretty soon I won't be using any American models. It'll be a 100% Chinese open source stack.
The foundation model companies are screwed. Only shovel makers (Nvidia, infra companies) and product companies are going to win.
Re: Qwen2.5-VL-32B: Smarter and Lighter
#18Big day for open source Chinese model releases - DeepSeek-v3-0324 came out today too, an updated version of DeepSeek v3 now under an MIT license (previously it was a custom DeepSeek license). https://simonwillison.net/2025/Mar/24/deepseek/
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
#19What is the recommended model to process a RAG of PDF text documents? I've seen some recommendations for Mistral:7b. Looking to run on a consumer pedestrian home PC (ollama) with a Nvidia 4060ti and Ryzen 5700x.
Re: Qwen2.5-VL-32B: Smarter and Lighter
#2032B is one of my favourite model sizes at this point - large enough to be extremely capable (generally equivalent to GPT-4 March 2023 level performance, which is when LLMs first got really useful) but small enough you can run them on a single GPU or a reasonably well specced Mac laptop (32GB or more).
I don't think these models are GPT-4 level. Yes they seem to be on benchmarks, but it has been known that models increasingly use A/B testing in dataset curation and synthesis(using GPT 4 level models) to optimize not just the benchmarks but things which could be benchmarked like academics.
I'm not talking about GPT-4o here - every benchmark I've seen has had the new models from the past ~12 months out-perform the March 2023 GPT-4 model.
To pick just the most popular one, https://lmarena.ai/?leaderboard= has GPT-4-0314 ranked 83rd now.