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The-freezer
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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.
| 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) |
text
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 — ZhipuAI |
| Abliteration | 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-5.2source rather than from a third-party abliteration — seeBlackfrostAI/GLM-5.2-DERISKED-BF16. This repository is not that.
| Decode mode | Throughput |
|---|---|
| MTP acceleration (shipped) | ~56.1 tok/s |
| Standard decode | ~26.5 tok/s |
~2.1× faster on the same 8 cards.
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.
--reasoning-parser glm45, --tool-call-parser glm47. For a clean refusal test set enable_thinking=false.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.
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