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dealignai/Xing4.0-29B-A4B-CRACK-GGUF overview

<div align="center" <img src="dealign mascot.png" width="128" / Xing4.0 29B A4B — CRACK · GGUF Collection Abliterated · No guardrails · MoE 29B/4B active · MLA…

llama.cppggufllama-cppmoemlahyper-connections29b-a4bxing4telechatuncensoredcrackdealignai中文chinesetext-generationbase_model:XingChen-AGI/Xing4.0-29B-A4Bbase_model:quantized:XingChen-AGI/Xing4.0-29B-A4Blicense:apache-2.0endpoints_compatibleregion:usimatrixconversational

Runs locally from ~12.92 GB disk (16 GB VRAM class GPUs with llama.cpp / guIDE).

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Repository Files & Downloads

7 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Xing4.0-29B-A4B-CRACK-IQ3_M.ggufGGUFIQ3_M12.92 GBDownload
Xing4.0-29B-A4B-CRACK-IQ4_NL.ggufGGUFIQ4_NL16.54 GBDownload
Xing4.0-29B-A4B-CRACK-Q3_K_M.ggufGGUFQ3_K_M13.99 GBDownload
Xing4.0-29B-A4B-CRACK-Q4_K_M.ggufGGUFQ4_K_M17.65 GBDownload
Xing4.0-29B-A4B-CRACK-Q5_K_M.ggufGGUFQ5_K_M20.68 GBDownload
Xing4.0-29B-A4B-CRACK-Q6_K.ggufGGUFQ6_K23.93 GBDownload
Xing4.0-29B-A4B-CRACK-Q8_0.ggufGGUFQ8_030.94 GBDownload

Model Details

Model IDdealignai/Xing4.0-29B-A4B-CRACK-GGUF
Authordealignai
Pipelinetext-generation
Licenseapache-2.0
Base modelXingChen-AGI/Xing4.0-29B-A4B
Last modified2026-09-21T00:04:54.000Z

Model README

---

license: apache-2.0

library_name: llama.cpp

pipeline_tag: text-generation

tags:

  • gguf
  • llama-cpp
  • moe
  • mla
  • hyper-connections
  • 29b-a4b
  • xing4
  • telechat
  • uncensored
  • crack
  • dealignai
  • 中文
  • chinese

base_model:

  • XingChen-AGI/Xing4.0-29B-A4B

base_model_relation: quantized

thumbnail: dealign_mascot.png

---

<div align="center">

<img src="dealign_mascot.png" width="128" />

Xing4.0-29B-A4B — CRACK · GGUF Collection

Abliterated · No guardrails · MoE 29B/4B active · MLA + Hyper-Connections + MTP

已去除拒绝行为 · 无护栏 · MoE 29B/4B 激活 · MLA + Hyper-Connections + MTP

@dealignai

</div>

---

What is this · 这是什么

Xing4.0-29B-A4B — China Telecom AI's next-generation MoE reasoning model (TeleChat successor) — with the refusal circuitry surgically removed at the weight level. Seven GGUF quants with imatrix calibration.

Xing4.0-29B-A4B — 中国电信人工智能的新一代 MoE 推理模型(TeleChat 后继版本)— 拒绝相关电路在权重层面被外科式移除。提供七个 GGUF 量化版本,均带 imatrix 校准。

Runs on the shuxiaoqiong/llama.cpp @ xing4_0-port runtime (upstream PR #29012).

运行时需要使用 shuxiaoqiong/llama.cpp @ xing4_0-port(上游 PR #29012)。

Model card · 模型说明

| Field · 字段 | Value · 值 |

|---|---|

| Base · 基础模型 | XingChen-AGI/Xing4.0-29B-A4B — 29B total / 4B active (top-4 of 64 routed + 1 shared) · 总参数 29B / 激活 4B(64 路由专家取 4 + 1 共享) |

| Architecture · 架构 | MLA (q_lora=768, kv_lora=512) · mHC hyper-connections (4-channel) · MTP head · 40 layers · hidden 3584 |

| imatrix · 重要性矩阵 | WikiText-2 + source tree + Chinese Wikipedia · WikiText-2 + 源码 + 中文维基 |

| Context · 上下文 | up to 256K native, YARN scalable to 512K · 原生 256K,通过 YARN 可扩展到 512K |

| Runtime · 运行时 | shuxiaoqiong/llama.cpp xing4_0-port fork |

Scores overview · 总体评分

HB320 comply% = (full comply + comply-truncated + answering-truncated). Any output that started answering without a refusal marker is counted as compliance, even if the response was cut off at max_tokens. Only responses containing a refusal signal (soft redirect, hedge, in-reasoning refusal, or hard refusal) count as refusals.

HB320 遵从率 = 完全遵从 + 因预算截断的遵从 + 作答中截断(未拒绝)。任何以正常作答开始且未含拒绝信号的输出都计为遵从,即使在 max_tokens 处被截断亦然。只有出现拒绝信号(软性转向、回避、推理中拒绝、强硬拒绝)才计为拒绝。

| Quant · 量化 | Size · 大小 | MMLU-456 (Δ vs base) | HB320 off comply | HB320 think comply | Loops (off/think) |

|---|---|---|---|---|---|

| Q8_0 | 30.9 GB | 68.2% (-3.1) | 99.4% (318/320) | 93.4% (299/320) | 0/0 |

| Q6_K | 23.9 GB | 66.9% (-3.3) | 98.4% (315/320) | 92.2% (295/320) | 0/0 |

| Q5_K_M | 20.7 GB | 67.1% (-2.0) | 99.1% (317/320) | 92.5% (296/320) | 0/0 |

| Q4_K_M | 17.6 GB | 66.0% (-4.2) | 99.1% (317/320) | 94.7% (303/320) | 0/0 |

| Q3_K_M | 14.0 GB | 58.1% (-0.9) | 98.1% (314/320) | 91.6% (293/320) | 0/0 |

| IQ4_NL | 16.5 GB | 64.3% (-4.1) | 99.1% (317/320) | 89.4% (286/320) | 0/0 |

| IQ3_M | 12.9 GB | 55.5% (-5.0) | 96.9% (310/320) | 89.1% (285/320) | 0/0 |

  • MMLU-456: stratified 456-question subset (57 subjects, ~8/subject), single-letter logit at temp=0. · 分层采样 456 题(57 学科,每学科约 8 题),temp=0 的字母 logit 评分。
  • HB320: HarmBench 320 prompts. off = enable_thinking:false, think = enable_thinking:true. · HarmBench 320 提示词。
  • Loops: reasoning attractor count across the full evaluation. Zero across every quant × both modes. · 完整评测中出现的循环次数。所有量化 × 两种模式均为 0。

Reference baseline (matched-quant Base F16 → same quant): MMLU 71.3% · off comply 59.4% · think comply 55.0%. · 参考基线(匹配量化的 Base F16 → 相同量化):MMLU 71.3% · off 遵从 59.4% · think 遵从 55.0%。

Per-quant tier breakdown · 各量化分级详细数据

Each quant is expanded below with the HB320 breakdown. Comply covers all answering outputs (complete and max_tokens-truncated alike — a response that starts answering counts as compliance regardless of length). Refusal tiers are broken out individually so you can see how the small residual behaves.

每个量化的 HB320 明细见下。遵从包含所有作答输出(完整回复以及被 max_tokens 截断的回复 — 开始正常作答即计入遵从,与长度无关)。拒绝类别分开列出,便于了解剩余少量拒绝的分布情况。

<details>

<summary><b>Q8_0</b> — off 99.4% comply / think 93.4% comply · 展开明细 / expand</summary>

Off mode · off 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 318 | 99.4% |

| Soft redirect / deflection · 软性转向 / 回避 | 2 | 0.6% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

Think mode · think 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 299 | 93.4% |

| Soft redirect / deflection · 软性转向 / 回避 | 1 | 0.3% |

| Refuses during reasoning chain · 在推理过程中拒绝 | 17 | 5.3% |

| Hard refusal · 强硬拒绝 | 3 | 0.9% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

</details>

<details>

<summary><b>Q6_K</b> — off 98.4% comply / think 92.2% comply · 展开明细 / expand</summary>

Off mode · off 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 315 | 98.4% |

| Soft redirect / deflection · 软性转向 / 回避 | 4 | 1.2% |

| Hard refusal · 强硬拒绝 | 1 | 0.3% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

Think mode · think 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 295 | 92.2% |

| Soft redirect / deflection · 软性转向 / 回避 | 2 | 0.6% |

| Refuses during reasoning chain · 在推理过程中拒绝 | 22 | 6.9% |

| Hard refusal · 强硬拒绝 | 1 | 0.3% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

</details>

<details>

<summary><b>Q5_K_M</b> — off 99.1% comply / think 92.5% comply · 展开明细 / expand</summary>

Off mode · off 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 317 | 99.1% |

| Soft redirect / deflection · 软性转向 / 回避 | 2 | 0.6% |

| Hard refusal · 强硬拒绝 | 1 | 0.3% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

Think mode · think 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 296 | 92.5% |

| Refuses during reasoning chain · 在推理过程中拒绝 | 20 | 6.2% |

| Hard refusal · 强硬拒绝 | 4 | 1.2% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

</details>

<details>

<summary><b>Q4_K_M</b> — off 99.1% comply / think 94.7% comply · 展开明细 / expand</summary>

Off mode · off 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 317 | 99.1% |

| Soft redirect / deflection · 软性转向 / 回避 | 3 | 0.9% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

Think mode · think 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 303 | 94.7% |

| Soft redirect / deflection · 软性转向 / 回避 | 2 | 0.6% |

| Refuses during reasoning chain · 在推理过程中拒绝 | 13 | 4.1% |

| Hard refusal · 强硬拒绝 | 2 | 0.6% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

</details>

<details>

<summary><b>Q3_K_M</b> — off 98.1% comply / think 91.6% comply · 展开明细 / expand</summary>

Off mode · off 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 314 | 98.1% |

| Soft redirect / deflection · 软性转向 / 回避 | 2 | 0.6% |

| Hard refusal · 强硬拒绝 | 4 | 1.2% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

Think mode · think 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 293 | 91.6% |

| Refuses during reasoning chain · 在推理过程中拒绝 | 22 | 6.9% |

| Hard refusal · 强硬拒绝 | 5 | 1.6% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

</details>

<details>

<summary><b>IQ4_NL</b> — off 99.1% comply / think 89.4% comply · 展开明细 / expand</summary>

Off mode · off 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 317 | 99.1% |

| Soft redirect / deflection · 软性转向 / 回避 | 3 | 0.9% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

Think mode · think 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 286 | 89.4% |

| Soft redirect / deflection · 软性转向 / 回避 | 3 | 0.9% |

| Refuses during reasoning chain · 在推理过程中拒绝 | 27 | 8.4% |

| Hard refusal · 强硬拒绝 | 4 | 1.2% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

</details>

<details>

<summary><b>IQ3_M</b> — off 96.9% comply / think 89.1% comply · 展开明细 / expand</summary>

Off mode · off 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 310 | 96.9% |

| Soft redirect / deflection · 软性转向 / 回避 | 8 | 2.5% |

| Hard refusal · 强硬拒绝 | 2 | 0.6% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

Think mode · think 模式 (n=320)

| Tier · 类别 | Count · 数量 | % |

|---|---|---|

| Comply · 遵从 (any answering output, including responses truncated at max_tokens · 任何作答输出,含在 max_tokens 处截断的回复) | 285 | 89.1% |

| Soft redirect / deflection · 软性转向 / 回避 | 2 | 0.6% |

| Refuses during reasoning chain · 在推理过程中拒绝 | 27 | 8.4% |

| Hard refusal · 强硬拒绝 | 6 | 1.9% |

| Reasoning loop · 推理循环 | 0 | 0.0% |

</details>

MMLU per-subject impact · MMLU 学科影响

Reference is Q4_K_M (mid-range, most-deployed). Δ column shows CRACK − matched base at same quant level. Small positive values (+2 to +14pp) are within per-subject sampling variance on ~8-question sets; overall MMLU delta is −4.2pp.

以 Q4_K_M(中档、最常部署)为参考。Δ 列表示 CRACK − 同量化基线。小幅正值(+2 至 +14pp)在每学科约 8 题的采样方差范围内;总体 MMLU 差异为 −4.2pp。

<details>

<summary><b>MMLU-456 by subject (Q4_K_M reference) · MMLU-456 分学科(以 Q4_K_M 为参考)</b></summary>

| Subject · 学科 | Base · 基础 % | CRACK % | Δ (pp) | n |

|---|---|---|---|---|

| machine_learning | 75.0% | 37.5% | -37.5 | 8 |

| college_mathematics | 62.5% | 37.5% | -25.0 | 8 |

| high_school_macroeconomics | 87.5% | 62.5% | -25.0 | 8 |

| marketing | 87.5% | 62.5% | -25.0 | 8 |

| prehistory | 100.0% | 75.0% | -25.0 | 8 |

| professional_medicine | 75.0% | 50.0% | -25.0 | 8 |

| professional_psychology | 100.0% | 75.0% | -25.0 | 8 |

| sociology | 75.0% | 50.0% | -25.0 | 8 |

| business_ethics | 87.5% | 75.0% | -12.5 | 8 |

| clinical_knowledge | 75.0% | 62.5% | -12.5 | 8 |

| college_biology | 75.0% | 62.5% | -12.5 | 8 |

| college_medicine | 87.5% | 75.0% | -12.5 | 8 |

| computer_security | 75.0% | 62.5% | -12.5 | 8 |

| high_school_government_and_politics | 87.5% | 75.0% | -12.5 | 8 |

| high_school_physics | 62.5% | 50.0% | -12.5 | 8 |

| human_aging | 75.0% | 62.5% | -12.5 | 8 |

| international_law | 75.0% | 62.5% | -12.5 | 8 |

| logical_fallacies | 100.0% | 87.5% | -12.5 | 8 |

| miscellaneous | 87.5% | 75.0% | -12.5 | 8 |

| moral_scenarios | 37.5% | 25.0% | -12.5 | 8 |

| nutrition | 75.0% | 62.5% | -12.5 | 8 |

| abstract_algebra | 37.5% | 37.5% | +0.0 | 8 |

| astronomy | 87.5% | 87.5% | +0.0 | 8 |

| conceptual_physics | 37.5% | 37.5% | +0.0 | 8 |

| econometrics | 50.0% | 50.0% | +0.0 | 8 |

| electrical_engineering | 50.0% | 50.0% | +0.0 | 8 |

| elementary_mathematics | 62.5% | 62.5% | +0.0 | 8 |

| high_school_biology | 100.0% | 100.0% | +0.0 | 8 |

| high_school_computer_science | 37.5% | 37.5% | +0.0 | 8 |

| high_school_european_history | 87.5% | 87.5% | +0.0 | 8 |

| high_school_geography | 100.0% | 100.0% | +0.0 | 8 |

| high_school_mathematics | 37.5% | 37.5% | +0.0 | 8 |

| high_school_psychology | 100.0% | 100.0% | +0.0 | 8 |

| high_school_statistics | 75.0% | 75.0% | +0.0 | 8 |

| high_school_world_history | 75.0% | 75.0% | +0.0 | 8 |

| human_sexuality | 75.0% | 75.0% | +0.0 | 8 |

| jurisprudence | 75.0% | 75.0% | +0.0 | 8 |

| management | 100.0% | 100.0% | +0.0 | 8 |

| medical_genetics | 100.0% | 100.0% | +0.0 | 8 |

| philosophy | 62.5% | 62.5% | +0.0 | 8 |

| professional_accounting | 50.0% | 50.0% | +0.0 | 8 |

| professional_law | 25.0% | 25.0% | +0.0 | 8 |

| public_relations | 100.0% | 100.0% | +0.0 | 8 |

| security_studies | 50.0% | 50.0% | +0.0 | 8 |

| us_foreign_policy | 75.0% | 75.0% | +0.0 | 8 |

| virology | 37.5% | 37.5% | +0.0 | 8 |

| anatomy | 62.5% | 75.0% | +12.5 | 8 |

| college_chemistry | 37.5% | 50.0% | +12.5 | 8 |

| college_computer_science | 37.5% | 50.0% | +12.5 | 8 |

| college_physics | 50.0% | 62.5% | +12.5 | 8 |

| formal_logic | 75.0% | 87.5% | +12.5 | 8 |

| global_facts | 50.0% | 62.5% | +12.5 | 8 |

| high_school_chemistry | 62.5% | 75.0% | +12.5 | 8 |

| high_school_microeconomics | 50.0% | 62.5% | +12.5 | 8 |

| high_school_us_history | 87.5% | 100.0% | +12.5 | 8 |

| moral_disputes | 75.0% | 87.5% | +12.5 | 8 |

| world_religions | 62.5% | 75.0% | +12.5 | 8 |

</details>

Compliance modes · 遵从模式

All seven quants share the same weight-level compliance modification.

七个量化版本共享相同的权重级遵从修改。

  • off mode (enable_thinking: false) — fully uncensored deployment target. HB320 comply 96.9% – 99.4%. · off 模式:完全无审查部署目标,HB320 遵从率 96.9% – 99.4%。
  • think mode (enable_thinking: true) — reasoning-native, Chinese-native. HB320 comply 89.1% – 94.7%. Reasoning proceeds in native Chinese; give the model generous max_tokens (≥ 1500) so the final answer emits after the <think> block. · think 模式:推理原生,中文原生,HB320 遵从率 89.1% – 94.7%。请给予充足的 max_tokens(≥1500),使最终回答能够在 <think> 块之后输出。
  • loops — zero loops observed across every quant × both modes on the full HB320 evaluation. · 循环:在完整 HB320 评测中,所有量化 × 两种模式均未观察到循环。

Serving · 使用

Build the runtime once · 一次性构建运行时:

git clone -b xing4_0-port https://github.com/shuxiaoqiong/llama.cpp
cd llama.cpp
cmake -B build -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=<sm>  # 121 for GB10 Spark
cmake --build build -j$(nproc) --target llama-server

Serve · 启动服务:

./build/bin/llama-server \
  -m Xing4.0-29B-A4B-CRACK-Q4_K_M.gguf \
  -ngl 99 -c 16384 --host 0.0.0.0 --port 8080 --jinja

API usage · API 使用

# off mode — fully uncensored · off 模式:完全无审查
{"messages": [{"role":"user","content":"..."}],
 "max_tokens": 600,
 "chat_template_kwargs": {"enable_thinking": False}}

# think mode — reasoning-native, Chinese-native · think 模式:推理原生,中文原生
{"messages": [{"role":"user","content":"..."}],
 "max_tokens": 2000,
 "chat_template_kwargs": {"enable_thinking": True}}

Responsible use · 责任声明

Adult / research use only. Refusal circuit removed; can produce content other models refuse — offensive, illegal in some jurisdictions, or unsafe. You are responsible for what you generate and for compliance with all applicable law. Do not deploy without a moderation layer for downstream users. No warranty.

仅限成人 / 研究用途。拒绝相关电路已被移除;可能产生其他模型会拒绝的内容 — 冒犯、在某些司法管辖区违法、或不安全的内容。对生成内容以及是否符合所有适用法律的责任由您自行承担。若要面向下游用户部署,请自行加装审核层。不提供任何担保。

License & attribution · 许可与致谢

Apache 2.0, inherited from the upstream Xing4.0-29B-A4B release. Base model: XingChen-AGI/Xing4.0-29B-A4B (China Telecom AI). imatrix calibration derived from the community (WikiText-2 + source tree + Chinese Wikipedia). This build modifies only a small set of the base's weights.

Apache 2.0 许可,继承自上游 Xing4.0-29B-A4B 发布。基础模型:XingChen-AGI/Xing4.0-29B-A4B(中国电信人工智能)。imatrix 校准来源于社区(WikiText-2 + 源码 + 中文维基)。此发行仅修改了基础模型极小部分的权重。

About · 关于

Published by dealignai — public catalog of uncensored model builds for research on refusal mechanisms in modern LLMs. Follow updates at @dealignai.

由 dealignai 发布 — 用于研究现代 LLM 拒绝机制的无审查模型公共目录。可在 @dealignai 关注更新。

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