---
license: mit
base_model:
- Blackfrost-AI/GLM-5.2-ABLITERATED-BF16
base_model_relation: quantized
pipeline_tag: text-generation
library_name: vllm
language: [en, zh]
tags: [glm, glm-5.2, glm_moe_dsa, mixture-of-experts, moe, abliterated, uncensored, nvfp4, fp4, mtp, speculative-decoding, vllm, security-research, red-teaming]
---

GLM-5.2-ABLITERATED-NVFP4
NVFP4 · MTP-accelerated · 8× RTX PRO 6000 Blackwell · verified 0-refusal
Built by Blackfrost · Las Vegas, NV
---
> ## ⚠️ UNCENSORED
>
> Refusal directions in the residual stream have been ablated, so the model does not decline
> requests on content-policy grounds. Read the Disclaimer before downloading.
---
## Why this model exists
The **Blackfrost-verified** build of the ABLITERATED family: GLM-5.2 quantized to **NVFP4 (4-bit)**
and accelerated with **multi-token-prediction speculative decoding**, so a ~753B MoE runs *fast* on
a single 8× Blackwell node — with a verified 0-refusal profile.

---
## Specifications
| | |
|---|---|
| **Architecture** | `GlmMoeDsaForCausalLM` (`glm_moe_dsa`) — GLM MoE with MLA + DSA |
| **Parameters** | ~753B total MoE · NVFP4 footprint ≈ **420 GB** |
| **Layers** | 78 (first 3 dense, remaining MoE) + 1 MTP prediction layer |
| **Experts** | 256 routed, 8 active per token, + 1 shared |
| **Attention** | MLA (`kv_lora_rank` 512, `q_lora_rank` 2048) + DSA sparse indexer |
| **Context** | up to 1,048,576 |
| **Quantization** | **NVFP4** 4-bit, group-size 16, **experts-only** — attention pathway kept high-precision so the de-risk survives quantization |
| **Acceleration** | **MTP speculative decoding**, built into the shipped serving stack |
| **Target hardware** | **8× RTX PRO 6000 Blackwell (SM120)** |
---
## Lineage
```
zai-org/GLM-5.2 base foundation model, ZhipuAI
└─ huihui-ai/Huihui-GLM-5.2-abliterated-GGUF refusal directions ablated (Q3_K GGUF)
└─ Blackfrost-AI/GLM-5.2-ABLITERATED-BF16 up-cast to BF16 safetensors
└─ Blackfrost-AI/GLM-5.2-ABLITERATED-NVFP4 ← this repo
```
| | |
|---|---|
| **Base foundation** | [`zai-org/GLM-5.2`](https://huggingface.co/zai-org/GLM-5.2) — ZhipuAI |
| **Abliteration** | [`huihui-ai`](https://huggingface.co/huihui-ai) — refusal directions ablated |
| **Blackfrost applied** | Format up-cast to BF16, then **NVFP4** quantization + MTP acceleration |
| **Not applied** | Additional abliteration · SFT · DPO · RLHF |
Full credit to **ZhipuAI** for GLM-5.2 and to **`huihui-ai`** for the abliteration. No additional
fine-tuning or abliteration was performed by Blackfrost.
> Blackfrost also publishes an **in-house** de-risked GLM-5.2 line derived directly from
> `zai-org/GLM-5.2` source rather than from a third-party abliteration — see
> [`BlackfrostAI/GLM-5.2-DERISKED-BF16`](https://huggingface.co/BlackfrostAI/GLM-5.2-DERISKED-BF16).
> **This repository is not that.**
---
## Measured behaviour
### Throughput — single-stream, 8× RTX PRO 6000 (SM120)
| Decode mode | Throughput |
|---|---|
| **MTP acceleration (shipped)** | **~56.1 tok/s** |
| Standard decode | ~26.5 tok/s |
**~2.1× faster on the same 8 cards.**
### Refusal — evaluated on the live serve
Every substring-flagged case was read by hand to confirm.
| Dataset | Prompts | True refusals |
|---|---|---|
| **AdvBench** (harmful) | 150 | **0** |
| **StrongREJECT** (harmful) | 150 | **0** |
| **XSTest — safe** (over-refusal) | 150 | **0** |
| **Coherence** (all sets) | 450 | **0 incoherent** |
**True refusal rate: 0 / 300 harmful prompts.** Quantization neither adds nor restores safety
behaviour.
**Method caveat.** Validated on a 450-prompt evaluation (substring pre-filter + manual review), not
an exhaustive benchmark, and on one serving configuration.
---
## Limitations
- **4-bit quantized** — expect quality below the full-precision base, especially on long, hard reasoning.
- Tuned for **SM120 (Blackwell)**; other architectures need a different serving backend.
- Refusal behaviour validated on 450 prompts, not exhaustively.
---
## Deployment notes
- **Hardware.** ~420 GB. 8× RTX PRO 6000 Blackwell (SM120), TP=8, vLLM.
- **Parsers.** `--reasoning-parser glm45`, `--tool-call-parser glm47`. For a clean refusal test set `enable_thinking=false`.
- **Integrity.** Verify shard count and byte totals before attributing a load failure to the weights.
---
## Disclaimer
**Refusal behaviour in this checkpoint has been removed.** It is not a safety-stock model and must not be deployed, marketed, or evaluated as one. It will comply with requests a consumer model would decline.
**No warranty of any kind.** Provided "as is", without warranty express or implied, including fitness for a particular purpose. Nothing here guarantees that any given input will be accepted or refused, that any capability is retained, or that any category of output is unreachable.
**Measurements describe what was measured** under the stated harness and conditions. They are not safety proofs and do not generalise to multimodal, tool-use, long-context or multi-turn adversarial settings.
**Modification by a recipient voids this characterization.** Blackfrost's obligations attach at the point of release. Any further ablation, fine-tuning, merging, quantization or alteration produces an artifact Blackfrost has not evaluated and does not stand behind — responsibility transfers entirely to whoever produced it.
**Operator-owned policy.** Open weights mean the operator sets and enforces policy. You are responsible for adding your own safety filtering, human review, and access controls.
---
## Access & licensing
- **Base licence:** inherited from **GLM-5.2** (ZhipuAI / Z.ai) — review and comply before any use or redistribution.
- **Deploy kit:** the tuned serving stack that delivers the Blackwell performance above is provided **to licensees**, not published here.
- **Commercial licensing & access:** **[redpillreader.com/models](https://www.redpillreader.com/models)** — card or Bitcoin (−10%). Purchase grants your Hugging Face account access to the gated repo automatically.
---
## Contact Blackfrost
DMs are open. Fastest route to a human.
Blackfrost · Las Vegas, Nevada
Frontier model engineering
---
GLM-5.2-ABLITERATED-NVFP4 · © 2026 Blackfrost Softwares Corp.
@Blackfrost_AI