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To test: https://chat.qwen.ai/ https://chat.qwen.ai/ and select Qwen2.5-plus, then toggle QWQ.
by Leary 2y ago
To test: https://chat.qwen.ai/ https://chat.qwen.ai/ and select Qwen2.5-plus, then toggle QWQ.
- bangaladore 2y agoThey baited me into putting in a query and then asking me to sign up to submit it. Even have a "Stay Logged Out" button that I thought would bypass it, but no. I get running these models is not cheap, but they just lost a potential customer / user.
- deleted 2y ago[deleted]
- mrshu 2y agoYou can also try the HuggingFace Space at https://huggingface.co/spaces/Qwen/QwQ-32B-Demo https://huggingface.co/spaces/Qwen/QwQ-32B-Demo (though it seems to be fully utilized at the moment)
- zamadatix 2y agoRunning this model is dirt cheap, they're just not chasing that type of customer.
- doublerabbit 2y agoCheck out venice.ai They're pretty up to date with latest models. $20 a month
- fsndz 2y agosuper impressive. we won't need that many GPUs in the future if we can have the performance of DeepSeek R1 with even less parameters. NVIDIA is in trouble. We are moving towards a world of very cheap compute: https://medium.com/thoughts-on-machine-learning/a-future-of-cheap-compute-7be643af7923?sk=b5fd602d8e206cdfc128654980b94a92 https://medium.com/thoughts-on-machine-learning/a-future-of-...
- holoduke 2y agoHave you heard of Jevons paradox? That says that whenever new tech is used to make something more efficient the tech is just upscaled to make the product quality higher. Same here. Deepseek has some algoritmic improvements that reduces resources for the same output quality. But increasig resources (which are available) will increase the quality. There will be always need for more compute. Nvidia is not in trouble. They have a monopoly on high performing ai chips for which demand will at least rise by a factor of 1000 upcoming years (my personal opinion)
- UncleOxidant 2y agoI agree that the Jevons paradox can apply here, however, there have been several "breakthroughs" in the last couple of months (R1, diffusion LLMs, this) that really push the amount of GPU compute down such that I think it's going to be problematic for companies that went out and bought boatloads of GPUs (like OpenAI, for example). So while it might not be bad news for NVidia (given Jevons) it does seem to be bad news for OpenAI.
- ithkuil 2y agoI don't quite understand the logic. Even if you have cheaper models if you have tons of compute power you can do more things than if you had less compute power! You can experiment with huge societies of agents, each exploring multitude of options. You can run world models where agents can run though experiments and you can feed all this back to a single "spokesperson" and you'll have an increase in intelligence or at the very least you'll able to distill the next generation models with that and rinse and repeat. I mean I welcome the democratizing effect of this but I fail to understand how this is something that is so readily accepted as a doom scenario for people owning or building massive compute. If anything, what we're witnessing is the recognition that useful stuff can be achieved by multiplying matrices!
- fsndz 2y agoyeah, sure, I guess the investors selling NVIDIA's stock like crazy know nothing about jevons
- cubefox 2y agoHow do you know this model is the same as in the blog post?
- Alifatisk 2y agoThey have a option specifically for QwQ-32B now
- attentive 2y agoit's on groq now for super fast inference