arxiv arXiv cs.CL · 1h ago · research

Solar Open 2 Technical Report

from English

The Solar Open 2 Technical Report introduces Solar Open 2, a 250B-A15B Mixture-of-Experts language model designed for long-horizon agentic tasks. It achieves a 1M-token context window through a hybrid attention stack and is trained using efficient initialization from Solar Open 1 and curated high-value data.

The model utilizes a hybrid attention mechanism with one softmax layer among every three linear-attention layers, employing no positional encoding and a gated delta rule extended to negative eigenvalues.
Training efficiency is achieved by initializing from the shared skeleton of Solar Open 1 and refining a 20T data pool into a 10T mixture via quality- and rarity-aware curation.
Agent skills are consolidated from twelve domain specialists using Multi-teacher On-Policy Distillation (MOPD).
Solar Open 2 leads comparably sized open-weight models on MMLU-Pro, LiveCodeBench, and the APEX-Agents suite, while remaining competitive with DeepSeek-V4-Flash and MiMo-V2.5.
On Korean benchmarks, it records the highest average among compared models and is competitive with DeepSeek-V4-Pro at less than a sixth of its size.

The report highlights Solar Open 2's ability to hold entire agent trajectories in a single context while maintaining high performance across English and Korean benchmarks.

Importance 2/3 arXiv cs.CL Upstage AI agents Research paper

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