GoKawiilQuasar 438B is our flagship reasoning model, built for enterprise-scale agents and coding. It is the first large model Multiverse Computing has released, it runs in English and Spanish, and it scores 43 on the Artificial Analysis Intelligence Index, the highest result of any European model in the field.
The Intelligence Index v4.1.1 combines nine evaluations: GDPval-AA v2, τ³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience and AA-LCR. Quasar's 43 puts it ahead of Mistral Medium 3.5 at 30, NVIDIA Nemotron 3 Ultra at 38 and Inkling at 42, in a field led by Claude Opus 5 at 63.
Quasar is not only intelligent, it is also fast. It returns 500 tokens, thinking time included, in 15.3 seconds. Only three models in the comparison are faster, and only one of those, Gemini 3.7 Flash, scores higher on the index. Of the models that do outscore Quasar, only two answer in under 25 seconds. The rest take between 38 and 156.
Multiverse Computing has built its position on making AI more efficient and deployable. Quasar brings that work into the 400B-plus parameter class: a reasoning model for multi-step tasks that need planning, tool use, code execution and large context, without the latency that class normally carries.
The model is available through the CompactifAI API, so teams can test it without standing up infrastructure.
The highest-scoring European model
Figure 1. Artificial Analysis Intelligence Index v4.1.1, a composite of nine evaluations. Higher is better.
Quasar scores 43 on the composite index. That is 13 points ahead of Mistral Medium 3.5 and 5 ahead of Nemotron 3 Ultra, which carries 112 billion more parameters.
Frontier-class speed
Figure 2. End-to-end response time: seconds to output 500 tokens, including reasoning time. Lower is better.
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