---

license: mit

library_name: hebrus

pipeline_tag: text-generation

base_model: zai-org/GLM-5.2

base_model_relation: quantized

language:

• en
• zh

tags:

• hebrus
• gguf
• glm-dsa
• glm-5.2
• apple-silicon
• metal
• q2-k
• moe
• expert-major

inference: false

---

GLM-5.2 — Hebrus ExpertMajor v2

This repository publishes the qualified GLM-5.2 artifact for

andreaborio/hebrus, a source-built

Apple Metal inference engine with bounded SSD expert streaming.

The routed MoE bank is stored once in an embedded, checksummed

ds4.expert_major.v2 store. The DS4 token in the existing filename and the

serialized tensor identifier is a compatibility field; the runtime and

Hugging Face library name are Hebrus.

> This is a Hebrus-native GGUF extension, not a portable GGUF. Generic

> llama.cpp, MLX, Ollama, and hosted Hugging Face inference cannot execute it.

Qualified artifact

| Property | Value |

| --- | --- |

| Status | Current · Qualified pinned download; selected by Hebrus glm-v2 |

| File | GLM-5.2-DS4-ExpertMajor-v2-Q2_K.gguf |

| Hugging Face revision | ds4-v0.2.0, resolving to fa5a092f4e99913b3422046f6c626248996ba140 |

| Size | 262,147,193,504 bytes (244.14 GiB) |

| SHA-256 | 7f5017e3076e706c78f2a5322b035a9e2f6519c65ff5b6be8b2d91aeff61505d |

| Minimum unified memory | 64 GiB |

| Qualified normal mode | AUTO resolves to Metal SSD streaming |

| Normal starting context | 8,192 tokens |

| Recorded qualified frontier | 32,768 tokens; no 65K or 100K claim |

The legacy chunked diagnostic file and selected-hotlist sidecar under

legacy/ remain public for historical reproducibility only. Current Hebrus

rejects those layouts and does not use them as fallbacks.

Quick start

Requirements:

• an Apple Silicon Mac with at least 64 GiB unified memory;
• Xcode Command Line Tools;
• more than 262 GB of free local SSD space for the exact model file;
• the official Hugging Face CLI.

git clone https://github.com/andreaborio/hebrus.git
cd hebrus
git checkout v0.3.0

xcode-select --install
python3 -m pip install -U huggingface_hub hf_xet
make -j

./download_model.sh glm-v2

./hebrus \
  -m gguf/GLM-5.2-DS4-ExpertMajor-v2-Q2_K.gguf \
  --ctx 8192 \
  -p "Explain bounded SSD expert streaming in one paragraph."

The downloader pins ds4-v0.2.0 and verifies the complete byte count and

SHA-256. The repository is public and ungated, so downloading does not require

a Hugging Face token.

Normal AUTO startup resolves to the qualified SSD path. A resident request is

rejected even on a larger host. Do not add a sidecar, preload policy, manual

cache size, model-admission bypass, or backend flag.

Compatibility and limits

• Apple Silicon Metal with SSD streaming is the only qualified production

path for this artifact.

• The 64 GiB floor is not a promise that every context or concurrent workload

fits. Start at 8K; 32K has recorded evidence but is slow to test.

• No 65K or 100K GLM support claim is made by this release.
• CPU is reference/debug only. CUDA and ROCm sources are absent, and

distributed inference is retired.

• ExpertMajor v1, sidecars, the legacy chunked layout, canonical GGUF

inference, and admission bypasses are rejected.

• MTP/speculative decoding is not part of the qualified GLM startup path.
• Performance depends on the exact artifact, runtime revision, context,

prompt, storage state, memory pressure, routing locality, and thermals.

• inference: false is deliberate: the Hub hosted inference widget does not

support this runtime-specific artifact.

See the authoritative

runtime support contract

and the scoped

32K evidence.

License and attribution

The upstream zai-org/GLM-5.2

repository declares the MIT license. Z.ai retains the base-model copyright.

Historical runtime work credits antirez/DS4; the embedded ExpertMajor v2

release and current runtime are maintained by Hebrus.