Context : In March 2018 , ( ) reported the detection by VERITAS of very-high-energy emission ( VHE; > 100 { GeV } ) from 3C 264 .
This is the sixth , and second most distant , radio galaxy ever detected in the TeV regime .

Aims : In this article we present a radio and X-ray analysis of the jet in 3C 264 .
We determine the main physical parameters of the parsec-scale flow and explore the implications of the inferred kinematic structure for radiative models of this \gamma -ray emitting jet .

Methods : The radio data set is comprised of VLBI observations at 15 GHz from the MOJAVE program , and cover a time period of about two years .
Through a segmented wavelet decomposition method ( WISE code ) we estimate the apparent displacement of individual plasma features ; we then perform a pixel-based analysis of the stacked image to determine the jet shape .
The X-ray data set includes all available observations from the Chandra , XMM , and Swift satellites , and is used , together with archival data in the other bands , to build the SED .

Results : Proper motion is mostly detected along the edges of the flow , which appears strongly limb-brightened .
The apparent speeds increase as a function of distance from the core up to a maximum of { \sim } 11.5 c .
This constrains the jet viewing angle to assume relatively small values ( \theta \lesssim 10 ^ { \circ } ) .
In the acceleration region , extending up to a de-projected distance of { \sim } 4.8 \times 10 ^ { 4 } Schwarzschild radii ( { \sim } 11 pc ) , the jet is collimating ( r \propto z ^ { 0.40 \pm 0.04 } ) , as predicted for a magnetically-driven plasma flow .
By assuming that the core region is indeed magnetically dominated ( U _ { B } / U _ { e } > 1 ) , the SED and the jet power can be well reproduced in the framework of leptonic models , provided that the high-energy component is associated to a second emitting region .
The possibility that this region is located at the end of the acceleration zone , either in the jet layer or in the spine , is explored in the modeling .

Conclusions :