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New flagship reasoning model strengthens Europe’s sovereign AI capability, combining a score of 43 with a 15.3-second response time for enterprise agents and coding
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SAN SEBASTIÁN, Spain, Sept. 02, 2026 (GLOBE NEWSWIRE) — Multiverse Computing, a leader in compressed AI models, today announces the launch of Quasar 438B, its flagship reasoning model for enterprise-scale agents and coding.
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Quasar is the first large model released by Multiverse Computing. It supports English and Spanish and scores 43 on Artificial Analysis Intelligence Index v4.1.1, the highest result achieved by a European model in the comparison.
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The launch represents a significant step for European sovereign AI, demonstrating that Europe can compete with leading models from the US and China on capability and speed.
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The new model:
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- Outperforms Mistral Medium 3.5, which scores 30, and NVIDIA Nemotron 3 Ultra, which scores 38.
- Produces 500 output tokens in 15.3 seconds, including reasoning time. Only three models in the comparison are faster, and only one of them — Gemini 3.7 Flash — also records a higher Intelligence Index score. Quasar is faster than Mistral Medium 3.5, which takes 18.8 seconds, while delivering a 13-point higher score.
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That difference becomes particularly important in agentic systems. A single user request may require a model to plan a task, call several tools, check the results and adjust its approach. When an agent makes dozens of model calls to complete one piece of work, delays at each stage compound into minutes of additional waiting time. Quasar is designed to keep those loops moving while retaining the reasoning ability needed for complex work.
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The launch takes Multiverse Computing’s work on efficient, deployable AI into the 400-billion-plus parameter class. Quasar has 438 billion parameters, giving it the scale needed for demanding reasoning tasks while addressing the latency that can make very large models difficult to use inside interactive enterprise products.
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“This is a significant milestone for European AI: Quasar shows that European AI developers do not have to choose between reasoning performance and speed,” said Enrique Lizaso, co-founder and CEO of Multiverse Computing. “European enterprises need models that can work through complex tasks, use tools and handle long documents, and they also need greater choice and access to powerful AI developed here in Europe. Quasar brings those two requirements together in a model built for enterprise agents and coding.”
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Strong performance across long-context reasoning and coding
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Quasar scores 75.0 on Artificial Analysis Long Context Reasoning (AA-LCR), which tests a model’s ability to extract, connect and reason over information distributed across long documents. The result matches Grok 4.6 (high), comes within one point of Claude Opus 5 and leads Nemotron 3 Ultra by 4.0 points and Mistral Medium 3.5 by 9.7 points.