OpenAI's decision endpoint, announced at DevDay 2026. It focuses GPT-6 Luna on developer-defined questions that have a finite set of predefined answers, with text or image context, for classification, routing and an agent's next action.
Metask Lab's calibrated decision model in 16 languages. Qwen3.5-4B with a merged LoRA trained with the Nimble candidate-logit objective; one forward pass and a softmax over at most 26 answer-letter logits, with one temperature per question type.
Decides
choice, classify, route
choice, score, noul, classify, route
Architecture
gpt-6-luna
metask-jev
Fine-tuned from
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qwen/qwen3.5-4b
License
proprietary
apache-2.0
Availability
Hosted API
Open weights
Hosted by
OpenAI
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Input price
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Decision accuracy
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80.1%
Calibration error
—
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Valid action rate
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Median latency
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62.8 ms
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 decisions-api and metask-jev?
decisions-api is from OpenAI and metask-jev from Metask Lab. decisions-api is only available as a hosted API; metask-jev has open weights you can download and run. Both answer choice, classify and route questions. Only metask-jev answers score and noul. decisions-api is licensed proprietary; metask-jev, apache-2.0.
Which is more accurate, decisions-api or metask-jev?
Only metask-jev publishes an accuracy figure (80.1% on JevBench v1.2 public set (231 items) at 4,096 tokens, maker's run); decisions-api does not, so there is no comparison to make without your own test.
Which is cheaper, decisions-api or metask-jev?
decisions-api: Hosted, price not published. metask-jev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run decisions-api or metask-jev locally?
metask-jev yes — systemone pull metask-lab/metask-jev downloads its weights. The other is only served as a hosted API.
Evaluation suite
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JevBench v1.2 public set (231 items) at 4,096 tokens, maker's run
