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
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。
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% |
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% |
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% |
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% |
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% |
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% |
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% |
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。
| 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 |
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 generousmax_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。