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.
meraGPT's hosted decision model (state-decider-1). Answers yes/no, choice and rubric-score questions over one state as calibrated distributions in a single pass, on the System One schema, so the typesafe-sdk works by changing its base URL.
Decides
choice, score, noul, rank, classify, route
choice, score, noul, classify, route
Architecture
clm
state-decider
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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meraGPT
Input price
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$0.030/MTok
Decision accuracy
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76.8%
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 state-decider-1?
clm is from Contrastive-LM and state-decider-1 from meraGPT. clm has open weights you can download and run; state-decider-1 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; state-decider-1, proprietary.
Which is more accurate, clm or state-decider-1?
Only state-decider-1 publishes an accuracy figure (76.8% on typed-decisions benchmark (400 cases, 2,000 decisions; teacher-ensemble references), single run); clm does not, so there is no comparison to make without your own test.
Which is cheaper, clm or state-decider-1?
clm: Free (open weights). state-decider-1: $0.03 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Can I run clm or state-decider-1 locally?
clm yes — systemone pull contrastive-lm/clm downloads its weights. The other is only served as a hosted API.
Evaluation suite
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typed-decisions benchmark (400 cases, 2,000 decisions; teacher-ensemble references), single run
