Reflection AI is preparing an open-weight model, but its scale is still unknown.
Sh0ny
5 October 20261 min read
In short
The emergence of another American open-weight model could add competition for DeepSeek and Qwen. But for those running models locally, the main question remains unanswered: how much memory will it require?
Another open-weight player that could intensify competition with DeepSeek and Qwen. For those who run models locally, the focus will be not on the loud promise of a “powerful” model, but on its size and memory requirements.
A post on LocalLlama says that Reflection AI is preparing to release a model with open weights. The discussion’s author hopes it will be smaller than 200 billion parameters, but that is merely a wish, not a stated specification.
If the model is compact enough, people without powerful server hardware may be able to try it. For now, this is only a possible scenario: there is no data to assess the model’s practical accessibility.
The limitation is simple: the original post provides neither the model’s size, benchmark results, nor release conditions. The link to an Axios article in the post leads to an article that, according to the discussion’s author, is paywalled. So for now, it is impossible to tell how competitive the model will actually be or whether a typical home computer will be able to run it.
What size local model are you willing to run on your computer? Source: LocalLlama