GLM-5.3 is live. Run Z.ai's latest model on Friendli Model APIs. Try it today ➜
MingZwhy
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Run this model inference with full control and performance in your environment.
Model Details
Model Provider
MingZwhy
Model Tree
Qwen/Qwen3-0.6B
Input Modalities
Output Modalities
Supported Functionality
The tensors here are bf16 and not quantized. Quantization-aware training keeps high-precision master weights and applies the quantizer inside the forward pass; what gets saved is the master copy. Loading this file directly gives you an unquantized model. It will not error, and it will score higher than the W1.88 model does.
Use it as STUDENT_MODEL for the OPD stage, which supplies the quantizer
configuration itself:
bash
STUDENT_MODEL=<this checkpoint> bash scripts/opd/run_math.shFor a model you can load and evaluate, use the recovered checkpoint MingZwhy/Qwen3-0.6B-W1.88-QAOPD instead.
| weights | mixed INT1.58 / INT4 in blocks of 256, 12.5% of blocks at INT4 → 1.88 bits effective |
| embedding, output head | INT4 |
| activations | INT8 |
Apache-2.0, inherited from Qwen3-0.6B.