Wildland fires involve complicated processes that are challenging to represent in chemical transport models. Recent airborne measurements reveal remarkable chemical tomography in fresh wildland fire plumes, which remain yet to be fully explored using models. Here, we present a highresolution large eddy simulation model coupled to chemistry to study the chemical evolution in fresh wildland fire plume. The model is configured for a large fire heavily sampled during the Fire Influence on Regional to Global Environments and Air Quality field campaign, and a variety of airborne measurements are used to evaluate the chemical heterogeneity revealed by the model. We show that the model captures the observed cross-transect variations of a number of compounds quite well, including ozone (O3), nitrous acid (HONO), and peroxyacetyl nitrate. The combined observational and modeling results suggest that the top and edges of fresh plume drive the photochemistry, while dark chemistry is also present but in the lower part of the plume. The model spatial resolution is shown to be very important as it may shift the chemical regime, leading to biases in O3 and NOx chemistry. Based on findings in this work, we speculate that the impact of small fires on air quality may be largely underestimated in models with coarse spatial resolutions. Plain Language Summary Recent fire seasons in the United States have been record-setting for many states. Several large wildfires raged across the entire west coast and lofted smoke plumes spread to the majority of the continental U.S. From a scientific perspective, wildland fires are fascinating due to their complexity. Fires emit heat, creating a plume of hot and turbulent air. The fire plume also contains many gases and aerosol particles produced from the burning and baking of a variety of fuels on the ground (trees, grasses, leaf litter and other fallen debris, etc.). Many of these gases and aerosol particles can impact climate, air quality, and human health. For this reason, most modern air quality and climate models now consider wildland fires. However, wildland fires are fundamentally challenging for these models, because many fine-scale and large-scale processes are entangled at the same time. In this work, we use a high-resolution turbulence-resolving numerical model to study the fine details in a wildland fire plume, with implications for large-scale air quality and climate models.