Contrastive Language Models score a state against a set of candidate actions with a contrastive objective. Two projection heads on frozen Qwen3-8B embeddings, trained with InfoNCE; clm-serve maps Choice, Score and Noul onto candidate ranking.
Upstage's structured decision model, a System One endpoint on Solar Mini 4. Returns a choice, a score or a yes/no answer with a probability read from the model, in one forward pass, on the same /v1/systemone schema as Jev.
Decides
choice, score, noul, rank, classify, route
choice, score, noul, classify, route
Architecture
clm
solar
Fine-tuned from
qwen/qwen3-8b
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License
apache-2.0
proprietary
Availability
Open weights
Hosted API
Hosted by
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Upstage
Input price
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$0.10/MTok
Decision accuracy
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Calibration error
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Valid action rate
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Median latency
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p95 latency
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Figures are from each model’s manifest; accuracy and latency are what the publishers report, on their own suites and hardware. Add a third model.
Questions
What is the difference between clm and solar-decide?
clm is from Contrastive-LM and solar-decide from Upstage. clm has open weights you can download and run; solar-decide is only available as a hosted API. Both answer choice, score, noul, classify and route questions. Only clm answers rank. clm is licensed apache-2.0; solar-decide, proprietary.
Which is more accurate, clm or solar-decide?
Neither publishes an accuracy figure. Test both on your own labelled examples.
Which is cheaper, clm or solar-decide?
clm: Free (open weights). solar-decide: $0.1 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Can I run clm or solar-decide locally?
clm yes — systemone pull contrastive-lm/clm downloads its weights. The other is only served as a hosted API.
