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Solar Open 2 language model boasts 1M-token context window and strong agentic skills

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced Solar Open 2, a 250 billion parameter Mixture-of-Experts language model designed for long-horizon agentic tasks. This model features a 1 million token context window achieved through a hybrid attention mechanism and is trained efficiently using a stronger starting point and curated high-value data. Solar Open 2 demonstrates leading performance on several English benchmarks, including MMLU-Pro and the APEX-Agents suite, and shows competitive results against other top open-weight models. It also achieves top scores on Korean benchmarks and an in-house Korean officework-agent benchmark, outperforming larger models. AI

IMPACT Sets new SOTA on agentic benchmarks and demonstrates efficient training for large context windows.

RANK_REASON Technical report detailing a new language model release with benchmark results. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Solar Open 2 language model boasts 1M-token context window and strong agentic skills

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Technical report detailing a new language model release with benchmark results. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Sungrae Park (University of Seoul), Sanghoon Kim (University of Seoul), Gyoungjin Gim (University of Seoul), Jungho Cho (University of Seoul), Hyunwoong Ko (University of Seoul), Minbyul Jeong (University of Seoul), Minjeong Kim (University of Seoul), Ke… ·

    Solar Open 2 Technical Report

    arXiv:2607.20062v1 Announce Type: new Abstract: We present Solar Open 2, a 250B-A15B Mixture-of-Experts language model built for long-horizon agentic tasks, scaled up from Solar Open 1 (Solar Open 100B). To hold entire agent trajectories in a single context, Solar Open 2 reaches …

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