baa-ai/GLM-5.2-RAM-333GB-MLX

GLM-5.2 — 333GB (MLX)

Mixed-precision quantized version of zai-org/GLM-5.2 optimised by baa.ai using a proprietary Black Sheep AI method.

Per-tensor bit-width allocation via advanced sensitivity analysis and budget-constrained optimisation — no calibration data required.

Built at the efficiency knee (best quality-per-GB). Sized for 512GB Apple Silicon machines (333 GB model + headroom for OS/KV cache).

Metrics

Metric	Value
Size	333 GB
Average bits	3.58
Architecture	MoE (256 experts, MLA + sparse attention)

Usage

from mlx_lm import load, generate

model, tokenizer = load("baa-ai/GLM-5.2-RAM-333GB-MLX")
response = generate(model, tokenizer, prompt="Hello!", max_tokens=256)
print(response)

Requires a recent mlx-lm with GLM-DSA support. The chat template is embedded; GLM-5.2 supports a thinking mode.

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Quantized by baa.ai

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Black Sheep AI Products

Black Sheep AI builds private AI with the Bounded AI Architecture (BAA): three layers, each bound to something you control, on infrastructure you control. Nothing leaves your boundary.

Ram (Reasoning Layer) — Full-capability frontier models, shrunk to fit smaller GPUs with reasoning kept and certified. They rely strictly on your Data Modules for knowledge, so you swap the model as better ones ship.

Paddock (Knowledge Plane) — Binds your Data Modules directly to the reasoning layer: one per topic, period, person, permission or tenant. Permission, freeze, hand back or delete each one on its own.

Watchman (GRC Layer) — Governance, risk and compliance in a single, complete audit log: every module permission, every bind, every model's provenance. Five certificates before anything goes live.

Shepherd — Takes a frontier model, compresses it into a Ram reasoning model, certifies it with Watchman, binds it to your Paddock, and deploys the Bounded AI Architecture to your infrastructure: your cloud, a Mac Studio, or an air-gapped facility.

Learn more at baa.ai — Private AI for enterprises whose data cannot leave the building.