Model overview
Laguna-S-2.1-Uncensored-APEX-GGUF English | 📖 中文文档 Uncensored 118B-A8B MoE · abliterix Trial 16 · APEX I-tier GGUFs + imatrix Laguna S 2.1 is a poolside ~118B total / ~8B active per token Mixture-of-Experts model for agentic coding and long-horizon work. Architecture highlights: token-choice routing with softplus gates, 256 routed experts + 1 shared expert (top-10) , GQA, 1:3 global/sliding-window attention (48 layers: 12 global + 36 local, window 512), and up to about 1M context , with optional native thinking interleaved with tool use. This release builds on the official weights in two steps: Uncensored behavior edit via abliterix (ROCm + bitsandbytes 4-bit search path), selecting Trial 16 LoRA, stream-merged back to BF16, plus MoE safety-expert router bake-in. APEX mixed-precision GGUF quantized from the BF16 GGUF of our Laguna-S-2.1-Uncensored (converted with poolside llama.cpp (laguna) ), using APEX -style tensor-type configs + imatrix (token embedding / output kept at BF16 ).
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
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Estimate monthly base token costs
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Public benchmarks & run configuration
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。
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Sources & traceability
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。