https://github.com/deepseek-ai/DeepSeek-R1/...s/benchmark.jpg
Here is the comparison. The full 671b models need over 400GB of memory to run, which is out of reach for most people.

Distillation transfers the knowledge to smaller model (i.e. feeding the QA chain), but smaller model has way fewer parameters so they won't be generating result so well.

The list of distilled models:
- DeepSeek-R1-Distill-Qwen-1.5B
- DeepSeek-R1-Distill-Qwen-7B
- DeepSeek-R1-Distill-Llama-8B
- DeepSeek-R1-Distill-Qwen-14B
- DeepSeek-R1-Distill-Qwen-32B
- DeepSeek-R1-Distill-Llama-70B

32B can let you run on RTX5090 nicely with context (the QA chain is involved to generate further response), but how many of us can justify buying that 5 digits GPU + heavy TNB bill just to run this?

hey. any freelancer willing to do a bit coding for hire?

im planning to build a chatbot using deepseek for my online futsal court booking platform. API ready.
deepseek api cost is very attractive compare to chatgpt.

im a bit lazy to code on the side now.

different topic:
US tech stock dipped after deepseek blew up. but I think its a knee jerk reaction.

deepseek is open sourced. chatgpt and the likes can make reference and make changes to their codes. and with their massive AI chip that is only available to them.
its gonna come back MASSIVE.

its good for business and consumers. I think massive discount gonna come soon to chatgpt and the likes when are on par in term of cost with deepseek.

I think have a long position on US AI stocks is still a good look
thoughts?