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Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs

Andrea Sassella, Andrea Chizzola, Tommaso Bianchi, Luca Alessandrelli, Mark James Carman · May 8, 2026

Citations: 0

Match reason: Keyword overlap 3/3 across title and protocol fields.

Score: 71% Sparse protocol signal Freshness: Cold Status: Ready
Math
  • This report benchmarks the performance of ENGINEERING Ingegneria Informatica S.p.A.'s EngGPT2MoE-16B-A3B LLM, a 16B parameter Mixture of Experts (MoE) model with 3B active parameters.
  • Performance is investigated across a wide variety of representative benchmarks, and is compared against comparably-sized open-source MoE and dense models.
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