EXAONE-4.5-33B

モデル紹介

We introduce EXAONE 4.5, the first open-weight vision language model developed by LG AI Research. Integrating a dedicated visual encoder into the existing EXAONE 4.0 framework, we expand the model's capability toward multimodality. EXAONE 4.5 features 33 billion parameters in total, including 1.2 billion parameters from the vision encoder. EXAONE 4.5 achieves competitive performance in general benchmark while outperforming SOTA models of similar size in document understanding and Korean contextual reasoning, inheriting powerful language capabilities from our previous language models. For more details, please refer to the technical report, blog and GitHub. - Model Type: Causal Language Model + Vision Encoder - Number of Parameters (Language Model): 31.7B - Number of Parameters (Vision Encoder): 1.29B - Hidden Dimension: 5,120 - Intermediate size: 27,392 - Number of Layers: 64 Main layers + 1 MTP layers - Hybrid Attention Pattern: 16 x (3 Sliding window attention + 1 Global attention) - Reordered Norm: Apply normalization after Attention/MLP, and before residual connection - Sliding Window Attention - Number of Attention Heads: 40 Q-heads and 8 KV-heads - Head Dimension: 128 for both Q/KV - Sliding Window Size: 4096 - Global Attention - Number of Attention Heads: 40 Q-heads and 8 KV-heads - Head Dimension: 128 for both Q/KV - No Rotary Positional Embedding Used (NoPE) - Vision Encoder - Grouped Query Attention (GQA) - 2D RoPE for vision embeddings - Vocab Size: 153,600 - Context Length: 262,144 tokens - Knowledge Cutoff: Dec 2024 (2024/12)

主な特徴

特点摘要待依据来源补齐，不凭模型名称推断能力。

制約と注意点

具体的な制約を判断する出典が不足しています。実際の性能、遅延、データ方針、ライセンス、提供期間を確認してください。

出典別料金と費用分析

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公開評価と実行設定

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

よくある質問

出典と追跡記録

许可证：other。模型介绍与第三方评测均以原来源的具体版本和方法为准。