Syngas cleaning especially tar removal is the major techno-economical obstacle in the implementation of the gasification technology. Especially in small-scale applications, where economy of scale effects cannot be taken into account, complex syngas cleaning processes result in excessive specific plant costs. Hence, to limit efficiency losses and overall costs, process integration and design simplification are imperative in small-scale gasification plants. The aim of this contribution is the optimization and adaptation of gas cleaning concepts for small-scale biomass gasification processes. Two distinct tar removal technologies, namely medium temperature gas cleaning (MTGC) and cold gas cleaning (CGC), are combined with an allothermal and optionally pressurized steam gasifier, operating at a feedstock input of 1,3 MWth. The MTGC process removes tar components through steam reforming in a fixed bed reactor, containing conventional Ni-based steam reforming and methanation catalyst. The heat necessary for tar conversion is provided by the simultaneously proceeding methanation reaction. Thus the reactor operates in a considerably lower temperature range of 500 to 600 °C than conventional catalytic tar removal technologies. In contrast, the syngas is cooled to temperatures under 200 °C in the CGC process. The tar species are separated physically through condensation and absorption in a packed bed scrubber using an organic scrubbing solvent. Currently this process is considered state of the art and implemented into several commercial biomass gasification plants. By means of process simulation, both gasification and syngas cleaning concepts were designed, thermally integrated and analyzed to optimize the efficiency and minimize the required amount of energy and consumables. The overall process was implemented into the equation oriented simulation tool IPSEpro, combining mathematical models of various syngas cleaning steps, developed by the user, and partially modified existing model units. Additionally, both gas cleaning methods were modeled in Aspen Plus, which allowed a more detailed and comprehensive evaluation of the individual components. Moreover, the use of Aspen Plus and related software products, particularly the Aspen Process Economic Analyzer, facilitated the economic evaluation, performed to compare the MTGC and the CGC process conclusively. The analysis of the overall system, performed in IPSEpro, shows that under optimized parameters a cold gas efficiency of approx. 70% can be reached by using MTGC. Using CGC an optimized cold gas efficiency of approx. 79% was calculated. By utilizing waste heat, the total efficiency of both processes can be increased to approx. 90%. To evaluate the influence of important process parameters on the overall process as well as on individual components and identify potential process improvements, both systems were subjected to a sensitivity analysis. The results of the parametric analysis illustrate that the steam excess ratio and especially the gasification pressure have a strong impact on the overall gasification and MTGC system. The efficiency and the required amount of consumables can be improved significantly by working under high gasification pressures and low steam excess ratios. The overall process using CGC benefits from low steam excess ratios and high system pressures as well. The tar removal efficiency in the organic tar scrubber increases with high gasification pressures and low solvent temperatures. However, even under optimized parameters only approx. 85% of polyaromatic tar species and over 90% of heterocyclic components were removed in the scrubber simulation. Hence, the syngas cleaned in the CGC process is not suitable for synthesis applications. In contrast, catalytic tar reforming, as conducted in the MTGC process, achieves almost complete tar conversion and thus meets the requirements of SNG production. Finally, the costs of both gas cleaning systems were estimated. The economic analysis shows that under the assumptions made in this contribution CGC is considerably cheaper than MTGC. While the capital costs of both concepts are comparable, the operational costs of MTGC are extensive, making the gas cleaning process economically unfeasible under the simulation presumptions. However, the total costs of MTGC can be reduced significantly by limiting the catalyst cost. Hence further research is necessary to reduce catalyst deactivation and lower the respective syngas cleaning costs.