  This paper is dedicated to the new implicit unstructured coronal code
COCONUT, which aims at providing fast and accurate inputs for space weather
forecast as an alternative to empirical models. We use all 20 available
magnetic maps of the solar photosphere covering the date of the 2nd of July
2019 which corresponds to a solar eclipse on Earth. We use the same standard
pre-processing on all maps, then perform coronal MHD simulations with the same
numerical and physical parameters. In the end, we quantify the performance for
each map using three indicators from remote-sensing observations: white-light
total solar eclipse images for the streamers' edges, EUV synoptic maps for
coronal holes and white-light coronagraph images for the heliospheric current
sheet. We discuss the performance for space weather forecasts and we show that
the choice of the input magnetic map has a strong impact. We find performances
between 24% to 85% for the streamers' edges, 24% to 88% for the coronal hole
boundaries and a mean deviation between 4 to 12 degrees for the heliospheric
current sheet position. We find that the HMI runs are globally performing
better on all indicators, with the GONG-ADAPT being the second-best choice. HMI
runs perform better for the streamers' edges, GONG-ADAPT for polar coronal
holes, HMI synchronic for equatorial coronal holes and for the streamer belt.
We especially showcase the importance of the filling of the poles. This
demonstrates that the solar poles have to be taken into account even for
ecliptic plane previsions.
