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Rohan Paul· @rohanpaul_ai · X· · Original publication time AI score47

Thinking Machines Lab releases Inkling 2 Small model weightsMachine translation

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Inkling 2 Small is a 594B-parameter model trained with 4-bit forward passes. It is available for download on Hugging Face under an Apache 2.0 license. The source says 4-bit training cut pretraining time by 8% and RL time by 20%, with about a 2% efficiency loss; running it requires at least 500GB of GPU memory.

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@rohanpaul_ai

@thesimaximalist 😄😀

ReplyThe SI Maximalist@thesimaximalist
@rohanpaul_ai You slipped “594B” and “Small” into the same sentence so casually 😂
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Related contextRohan Paul@rohanpaul_ai
Thinking Machines Lab kept its promise and open-sourced Inkling 2 Small, a 594B-parameter model trained with 4-bit forward passes. > now available for download on HuggingFace under an Apache 2.0 licens > Training in 4-bit cut pretraining time 8% and RL time 20%, for about 2% efficiency loss. > Running it takes at least 500GB of GPU memory in NVFP4 and at least 800GB in MXFP8, and MXFP8 gains “a very marginal 1–2 percentage points” over NVFP4 on evals. > Because training kept the same numerics from pretraining through the final RL rollout, the released 4-bit checkpoint needed no separate calibration step. > The lab first tried NVFP4 in both forward and backward passes, but that hurt compute efficiency too much, so only the forward pass stays in 4-bit.
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