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Compactbot
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We're announcing KV1. Now. We're going to take some models, do a bit of continued training on them and QAT them for only a 2 bit KV cache. And because of what happened with BGA, and this is also kind of some research stuff, here's what we're going to change: We're going to always, before we release how and make any claims, release our results. We also would like (idk if we can) to have some external reviewers before releasing them, I'M talking to YOU @AtAndDev and @mithulaartigala And we're going to properly cite other research. The models we are going to release is: KV1 1.2B, based on LFM 2.5 1.2B Instruct KV1 2.6B, based on LFM 2.5 2.6B Instruct KV1 4B, based on Qwen3.5 4B. If we get enough compute, we may also train: KV1 9B And if you guys want to a ~27B model, you guys decide which, either on LFM 2.5 24B A2B, Qwen3.8 27B, or Qwen3.6 35B A3B. Our goal is to get 2 bit, at 4 bit quality. Here's an image of our current progress, KV1 is at 3 bit, not 4 bit, but it will improve!
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We're announcing KV1. Now. We're going to take some models, do a bit of continued training on them and QAT them for only a 2 bit KV cache. And because of what happened with BGA, and this is also kind of some research stuff, here's what we're going to change: We're going to always, before we release how and make any claims, release our results. We also would like (idk if we can) to have some external reviewers before releasing them, I'M talking to YOU @AtAndDev and @mithulaartigala And we're going to properly cite other research. The models we are going to release is: KV1 1.2B, based on LFM 2.5 1.2B Instruct KV1 2.6B, based on LFM 2.5 2.6B Instruct KV1 4B, based on Qwen3.5 4B. If we get enough compute, we may also train: KV1 9B And if you guys want to a ~27B model, you guys decide which, either on LFM 2.5 24B A2B, Qwen3.8 27B, or Qwen3.6 35B A3B. Our goal is to get 2 bit, at 4 bit quality. Here's an image of our current progress, KV1 is at 3 bit, not 4 bit, but it will improve!
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