Decision-1.0-Lux-9B

The 9B Decision 1.0 decoder on the Qwen3.5 backbone, the family's largest, for a GPU.

Property	Value
Repository	vllm-sr/Decision-1.0-Lux-9B, pinned at 2064c84daf59
Family	Decision 1.0
Parameters	7.94B loaded
Backbone	Qwen3.5 text
Precision (--dtype auto)	BF16 on a GPU, FP32 on a CPU
Weights	about 15.9 GB at BF16, 31.8 GB at FP32
Device memory	24 GiB or more
Reads	text

Question types

Type	Answers
choice	Yes
noul	Yes
score	Yes
set	Yes, asked as one noul per label
span	No: bind span questions, such as PII and hallucination, to a span-capable model

Built-in questions

The Decision 1.0 family answers the Router's built-in questions zero-shot, from their canonical wording; the support matrix shows what that covers.

note

This model has no calibrated thresholds: a built-in question without a predicate uses 0.5, and the configuration load warns with uncalibrated_preset.

Hardware

Each time it loads, the model compares its answers with the reference answers recorded for its revision. They are recorded for:

• CPU (cpu)
• NVIDIA Hopper (sm_90) (cuda:sm_90)
• AMD GPU (ROCm) (rocm)

Where a hardware reference and its device class's are both recorded, the hardware one is checked.

Choose a model lists the validated hardware.

Quantization

The runtime loads no quantized packages of the Decision 1.0 family: it runs at its published precision.

Deploy it

Serve it on its own in Engine mode, to ask it directly:

CPU

vllm-sr serve vllm-sr/Decision-1.0-Lux-9B --engine --platform cpu

Serve it on a CPU from the CPU image, as --platform cpu does: the ROCm image's PyTorch has no CPU LAPACK, which this backbone needs there.

AMD GPU

vllm-sr serve vllm-sr/Decision-1.0-Lux-9B --engine --platform rocm

NVIDIA GPU

vllm-sr serve vllm-sr/Decision-1.0-Lux-9B --engine --platform cuda

Or make it the Router's decision model:

config.yaml

global:
  model_catalog:
    deployments:
      primary:
        provider: model_runtime
        artifact: vllm-sr/Decision-1.0-Lux-9B
        device: auto
      spans:
        provider: model_runtime
        artifact: vllm-sr/vela3-fast
    bindings:
      pii: spans
      hallucination: spans
    system:
      decision_model: {deployment: primary}

device: auto takes the first validated GPU with enough free memory, else the CPU; name rocm:0 or cuda:0 to pin a GPU.

This model answers no span questions, so the example keeps pii and hallucination on a span-capable deployment; without those bindings a pii rule fails to load with span_required.

To run it on another host and attach the Router to it:

vllm-srun serve vllm-sr/Decision-1.0-Lux-9B --device auto --host 0.0.0.0 --port 8100

Then set endpoint: http://<host>:8100 and model: Decision-1.0-Lux-9B on the deployment; see Attach to a runtime you run.

Learn more

• Model card on Hugging Face
• decision1-parity record
• cuda-decision1-performance record
• Decision 1.0: the family's sizes and how they differ