QAT “quantization aware training” means they had it quantized to 4 bits during training rather than after training in full or half precision. It’s supposedly a higher quality, but unfortunately they don’t show any comparisons between QAT and post-training quantization.
The partnership with Ollama and MLX and LM Studio and llama.cpp was revealed in that announcement, which made the models a lot easier for people to use.
I'm literally asking, quite honestly, if this is just an 'after the fact' update literally weeks later, that they uploaded a bunch of models, or if there is something more significant about this I'm missing.
Last time we only released the quantized GGUFs. Only llama.cpp users could use it (+ Ollama, but without vision).
Now, we released the unquantized checkpoints, so anyone can quantize themselves and use in their favorite tools, including Ollama with vision, MLX, LM Studio, etc. MLX folks also found that the model worked decently with 3 bits compared to naive 3-bit, so by releasing the unquantized checkpoints we allow further experimentation and research.
TL;DR. One was a release in a specific format/tool, we followed-up with a full release of artifacts that enable the community to do much more.
