KRAFTON/Raon-1-nano
text-generation model by KRAFTON
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Model card & documentation
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Raon-1 nano is a dense language model with 1.5B effective parameters (3.1B total, including a 1.5B per-layer embedding table), developed by KRAFTON AI. It is designed to follow instructions, maintain conversational context, and call the right tools in both Korean and English. As part of the Raon open model family, it is released under the Apache 2.0 license. Raon-1 nano uses a hybrid dense architecture, consisting of 18 linear attention layers and 6 full attention layers. gates and a fixed-size recurrent state. hyper-connections (mHC), which speeds up training. After its MLP, the layer uses it to adjust its output before passing it on. Only the 6 MLA layers keep a KV cache, about 7 KiB per token in BF16. The checkpoint on HuggingFace contains 3.2B parameters: 3.1B for the main model and 55M for the Multi-Token Prediction (MTP) module. CategoryBenchmark Raon-1 nano(E1.5B) Qwen3.52B Gemma 4E2B MiniCPM52B LFM31.7B Total params(effective) 3.1B(E1.5B)…
Read the full model card ↗ · Preview checked 2026-11-12T10:19:20.274Z
Inside the original model card — Document outline
- Raon-1 nano
- Highlights
- Model Overview
- Training
- Benchmark Results
- Sampling parameters
- Quickstart
- BF16 (no quantization)
- License
- Hugging Face model card / README notice License - Apache 2.0
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Model overview
KRAFTON/Raon-1-nano is a text-generation model repository published by KRAFTON on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- transformers
- Recent downloads (30 days)
- 806
- Cumulative likes
- 90
- Hugging Face trending score
- 88
- Reported safetensors parameters
- 3,529,911,376
- Architecture
- Raon1NanoForCausalLM
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-29T05:38:14.000Z
- Last modified
- 2026-11-11T12:31:43.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-14T06:56:53.534Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.