Agents-A1-Uncensored-MTP-APEX-GGUF

模型介绍

Agents-A1-Uncensored-MTP-APEX English | 📖 中文文档 Uncensored 35B agentic MoE · APEX-quantized GGUFs + MTP + BF16 mmproj Agents-A1 is a 35B-parameter Mixture-of-Experts agentic model from InternScience , post-trained on top of Qwen3.5-35B-A3B via a three-stage paradigm: full-domain SFT → domain-level teacher training → multi-teacher multi-domain on-policy distillation. Despite operating in the ~35B model class, Agents-A1 delivers highly competitive performance against frontier-scale systems such as GPT-5.5, DeepSeek-V4-pro, and Kimi-K2.6 — achieving SOTA on Seal-0 (56.4), HiPhO (46.4), FrontierScience-Olympiad (79.0), IFBench (80.6), IFEval (94.8), and best-among-comparable on BrowseComp (75.5), XBench-DS-2510 (86.0), GAIA (96.0), SciCode (44.3), HLE (47.6), and MolBench-bind (56.8). This GGUF package includes the mmproj-Agents-A1-Uncensored-MTP-BF16.gguf vision projector for multimodal (image + text) capabilities with llama.cpp. MTP layers are extracted from Qwen3.5-35B-A3B and injected into Agents-A1's safetensors (see MTP Extraction & Injection section). License: Apache-2.0. This release merges the selected behavior-modification LoRA into the BF16 base before MTP injection and APEX quantization. The uncensored adaptation was produced with abliterix . It is intended to reduce refusal behavior and can produce responses that differ materially from the original model. Evaluation result 2 refusals / 100 prompts KL divergence 0.016058 Use responsibly: evaluate the model for your deployment context and apply appropriate safeguards.

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

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公开评测与运行配置

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。

常见问题

资料来源与可追溯记录

许可证：apache-2.0。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。