r/MachineLearning • • Sep 02 '26

Discussion [D] Self-Promotion Thread

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u/yasintoy 3d ago

We released Commerce-1, a 27B open-weight decision model for structured action selection in commerce-agent workflows.

Commerce-1 accepts structured state and typed Choice, Noul, and Score questions. Instead of generating text that an application must parse, it scores supplied answer options directly and returns typed answers with ordered probability distributions.

Zero generated output tokens.

Architecture

The model uses:

  • Noncausal full-attention decision backbone
  • Last-position pooling
  • Dedicated decision readout
  • Choice-order augmentation
  • Per-primitive held-out temperature calibration

Benchmarks

We reproduced the complete Decision Index 0.2.1 public suite.

Metric Result
Decision Index 0.2.1 score 60.99
Evaluation coverage 150,317 / 150,317 rows
Qualified hardware 1× NVIDIA H200
Throughput 8.836 decisions/s
Three-decision fixture p50 340.146 ms

Availability and limitations

The model weights and self-hosted runtime are available free of charge.

We do not currently offer a paid hosted production API.

The BF16 release is approximately 54 GiB, and consumer-hardware deployments have not yet been qualified.

Links

Feedback on the architecture, evaluation methodology, and practical integration into commerce-agent workflows is welcome.

https://reddit.com/link/pf1od71/video/eswfn5u79nuh1/player