d3-oQ4e

This model was quantized using oQ (oMLX v0.7.1) mixed-precision quantization with Improved oQe Quantization (jundot/omlx#4385).

A mixed-precision MLX checkpoint of vllm-sr/d3, the 27B multimodal decision model of Decision 3.0 from vLLM Semantic Router, built on Qwen/Qwen3.8-27B. It reads text or JSON with optional images and videos and returns a probability for every option of choice, yes/no and score questions without generating text. It includes the language backbone, the vision encoder and the code readout.

The code readout (readout.safetensors, FP32) and decision_config.json are copied unchanged from the source. oMLX serves this checkpoint through POST /v1/systemone; Decision 3.0 support (jundot/omlx#4470) is newer than oMLX v0.7.1.dev1.

The effective average is 4.880 bits/weight for the complete checkpoint.

Quantization and Bit Distribution

oQ4e allocates bits by measured layer sensitivity, then rounds each group with an importance matrix (128 samples x 512 tokens) and a weighted least-squares refit of its scale and bias.

Storage format Logical weights Share of total Tensor storage Effective bits/weight
Affine 4-bit, group 64 21.075B 80.790% 11.041 GiB 4.50
Affine 5-bit, group 64 4.547B 17.429% 2.911 GiB 5.50
BF16 0.463B 1.776% 0.863 GiB 16.00
FP32 0.001B 0.005% 0.005 GiB 32.00
Total 26.087B 100% 14.820 GiB 4.880

Storage Breakdown

Component Logical weights Storage
Language backbone 25.625B 14.986 GB / 13.957 GiB
Vision encoder 0.461B 0.921 GB / 0.858 GiB
Code readout 0.001B 0.005 GB / 0.005 GiB
Total 26.087B 15.913 GB / 14.820 GiB

License

Apache-2.0, following the source model. See LICENSE and NOTICE.

Downloads last month
141
Safetensors
Model size
26B params
Tensor type
U32
·
BF16
·
MLX
Hardware compatibility
Log In to add your hardware

4-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for Jundot/d3-oQ4e

Base model

Qwen/Qwen3.8-27B
Finetuned
vllm-sr/d3
Quantized
(8)
this model