Mistral 7B is 187x cheaper compared to GPT-4

Along with their colleagues Karan Girotra and Lennart Meincke, they staged an idea generation contest6 to come up with the best products for a college student that would cost $50 or less. It was the GPT-4 AI against 200 students. The students lost, and it wasn’t even close. AI was faster, obviously, generating a lot more ideas than the average pers

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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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4. Introducing Stable LM 3B: Bringing Sustainable, High-Performance Language Models to Smart Devices

Stability AI introduced Stable LM 3B, a high-performing language model designed for smart devices. With 3 billion parameters, it outperforms state-of-the-art 3B models and reduces operating costs and power consumption. The model enables a broader ran... See more

For the deployment side of things, we found that the performance of our training process was quite slow, especially when it gets into these large language models and when you train from scratch. MosaicML offers what's called programmatic optimization, which is not so much on the hardware side of things, but rather on the algorithmic side. Can you f... See more

However development time, and maintenance can offset these savings. Hiring skilled data scientists, machine learning engineers, and DevOps professionals can be expensive and time consuming. Using available resources for “reimplementing” solutions hinder innovation and lead to a lack of focus. Since You not longer work on improving your model or pro... See more