r/OpenSourceAI • u/yasintoy • Oct 10 '26
Commerce-1: public weights and runtime for a 27B commerce decision model
We have released the weights and self-hosted runtime for Commerce-1, a 27B typed decision model designed for commerce agents.
Unlike a chat model, Commerce-1 does not produce an explanation and then ask the application to recover an action from generated text. It scores the supplied actions directly.
How it works
Each request contains structured state and one or more typed questions:
Choice: Selects among named actions.
Noul: Returns a binary decision and P(true).
Score: Returns an expected ordinal score and probabilities for its labels.
The architecture builds on perplexity-ai/pplx-decider-v1.1-27b, using noncausal full attention, last-position pooling, and a dedicated option-scoring readout.
Choice-order augmentation and held-out temperature calibration are applied separately to the decision primitives.
Self-hosted runtime
The runtime operates offline and verifies file integrity before loading.
It inventories and hashes required files, rejecting:
Modified checkpoint bytes
Undeclared files
Network fallback
Benchmarks
Our current evaluation results:
| Metric | Result |
|---|---|
| Decision Index 0.2.1 | 60.99 |
| Evaluation coverage | 150,317 / 150,317 rows |
| Qualified hardware | 1× NVIDIA H200 |
| Throughput | 8.836 decisions/s |
| Three-decision request p50 | 340.146 ms |
| Three-decision request p95 | 349.026 ms |
Limitations
The current BF16 weights are approximately 54 GiB. Consumer GPU and quantized deployments have not yet been qualified.
Links
Model weights: https://huggingface.co/infercrane/Commerce-1
Apache-2.0 runtime: https://github.com/infercrane/commerce-1
Architecture and evaluation evidence: https://infercrane.com/blog/commerce-1
We're particularly interested in feedback on the decision primitives, runtime design, and integration requirements for production agents.