r/LocalLLaMA - Reddit

A rough analogy to the current LLM process is that making a new model is like baking a cake. You figure out your data and algorithms—like mixing the batter—and then you pretrain the model, that is, run it on a large number of computers for several months—like putting it in the oven—and then at the end you do some “post training”—like frosting and d... See more

The three dynamics above can help us understand DeepSeek's recent releases. About a month ago, DeepSeek released a model called "DeepSeek-V3" that was a pure pretrained model 3 — the first stage described in #3 above. Then last week, they released "R1", which added a second stage. It's not possible to determine everything about these models from th... See more

I followed this curiosity, to see if a tool that can generate something mostly not wrong most of the time could be a net benefit in my daily work. The answer appears to be yes, generative models are useful for me when I program. It has not been easy to get to this point. My underlying fascination with the new technology is the only way I have manag... See more

With many 🧩 dropping recently, a more complete picture is emerging of LLMs not as a chatbot, but the kernel process of a new Operating System. E.g. today it orchestrates: - Input & Output across modalities (text, audio, vision) - Code interpreter, ability to write & run… Show more

R1’s leap in capability and efficiency wouldn’t be possible without its foundation model, DeepSeek-V3, which was released in December 2024. V3 itself is big—671 billion parameters (by comparison, GPT4-o is rumored to be 1.8 trillion, or three times as big)—yet it’s surprisingly cost-effective to run. That’s because V3 uses a mixture of experts (MoE

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