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Pipe Network PIPE: Lançamento do Kimi K3 MLX Port
A Pipe Network lançou uma versão MLX de código aberto para o Kimi K3 no dia 28 de julho. Um conversor de streaming e a otimização do REAP reduzem o tamanho do modelo de 1,6 TB para cerca de 350 GB, possibilitando sua execução em um Mac Studio.
Data do evento: 28 de julho de 2026 UTC
Pipe Network
@pipenetwork
@pipenetwork
Run Kimi K3 on a Mac Studio 🫰
K3 is 2.8T parameters and 1.6TB on disk, which makes it impossible to run on Apple Silicon.
Until now.
Our MLX port is now open source: https://github.com/PipeNetwork/kimi-k3-mlx
To accomplish this, we solved two things:
1. We wrote a streaming converter that walks one layer at a time, so that mlx_lm doesn't need to materialize the whole model.
2. REAP pruning sits on top and scores all 896 experts against a calibration corpus to keep only ones your workload needs.
That's what brings K3 down to 350GB and inside a Mac Studio.
K3 is 2.8T parameters and 1.6TB on disk, which makes it impossible to run on Apple Silicon.
Until now.
Our MLX port is now open source: https://github.com/PipeNetwork/kimi-k3-mlx
To accomplish this, we solved two things:
1. We wrote a streaming converter that walks one layer at a time, so that mlx_lm doesn't need to materialize the whole model.
2. REAP pruning sits on top and scores all 896 experts against a calibration corpus to keep only ones your workload needs.
That's what brings K3 down to 350GB and inside a Mac Studio.
Pipe Network
@pipenetwork
@pipenetwork
Get the full recipe, converter, calibration and pruning scripts here: https://t.co/q3jf1q3GZG
Quants published on Hugging Face:
1. REAP73: https://t.co/FvuDPBAL6B
2. REAP80: https://t.co/DQx7he4jex
3. REAP73 specialized in Chinese + code: https://t.co/woJkmKhu2B
Quants published on Hugging Face:
1. REAP73: https://t.co/FvuDPBAL6B
2. REAP80: https://t.co/DQx7he4jex
3. REAP73 specialized in Chinese + code: https://t.co/woJkmKhu2B
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28 jul 16:38 (UTC)
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