Kimi K3

Size

2.8T

Published

Moonshot AI · Release date not pinned

Line

New parts in the block · after Kimi K2

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Source

Kimi K3 technical report @ 3cb39df · Kimi K2.5 report (arXiv 2602.02276v2), for the RL step · no training code is publishedHow to read

Draft fine-tuning step

X[B, T]Target model h[B, T, 3·7168]Feature fusion

f=W_{\mathrm{E3}}[h_l;h_m;h_h]

f[B, T, 7168]Draft layer

\times 7\ \text{steps}

q[B, T, V]p[B, T, V]LK loss

\mathcal L_{\mathrm{LK}}=-\log\Big(\sum_{x\in\mathcal {\htmlClass{vl-stream-v}{V}}}\min\big(p(x),{\htmlClass{vl-stream-q}{q}}(x)\big)\Big)

ℒ_LK[1]hatched band: not updated in this step · solid band: what this stage trains

Draft fine-tuning step

Draft input

tensor

One vector of the hidden size for each position: the draft’s input at the first of its seven steps. After it the draft reads its own outputs.

shape: $f$ [B batch, T positions, 7168 d]

Sources

Contextual evidence from Feature fusion

§4.1.4, Draft Model Fine-Tuning: the pre-trained MTP layer is fine-tuned into an EAGLE-3-style draft model, with the target model frozen and only the draft layer and its feature-fusion projection updated; the draft is unrolled for seven steps and, beyond the first, consumes its own outputs. The input concatenates the outputs of the 1st, 4th and final AttnRes blocks and projects them by a bias-free matrix W_E3 initialized [0 0 I]. The loss is L_LK = −log Σ_x min(p(x), q(x)) (eq. 16), at temperature 1, with no cross-entropy term.

draft · MoonshotAI/Kimi-K3 / k3_tech_report.pdf
Pinned revision 3cb39dfd32e5 ↗ · p. 14