Liquid AI's first decision model, served only through the Liquid API. Returns Choice, Score and Noul answers with probability distributions and zero output tokens, on the /v1/systemone request shape used by TypeSafe's SDK.
Shanghai AI Laboratory's multimodal decision model. A fine-tune of Qwen3.5-4B's language backbone (vision tower frozen) that answers up to 16 Choice, Score and Noul questions about a state and up to eight images in one forward pass, with a fitted calibration temperature.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
d1
intern-decision
Fine-tuned from
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qwen/qwen3.5-4b
License
proprietary
apache-2.0
Availability
Hosted API
Open weights
Hosted by
Liquid AI
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Input price
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Decision accuracy
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80.6%
Calibration error
—
—
Valid action rate
—
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Median latency
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44 ms
p95 latency
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44.6 ms
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 d1 and intern-decision?
d1 is from Liquid AI and intern-decision from InternLM (Shanghai AI Laboratory). d1 is only available as a hosted API; intern-decision has open weights you can download and run. Both answer choice, score, noul, classify and route questions. d1 is licensed proprietary; intern-decision, apache-2.0.
Which is more accurate, d1 or intern-decision?
Only intern-decision publishes an accuracy figure (80.6% on LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions)); d1 does not, so there is no comparison to make without your own test.
Which is cheaper, d1 or intern-decision?
d1: Hosted, price not published. intern-decision: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run d1 or intern-decision locally?
intern-decision yes — systemone pull internlm/intern-decision downloads its weights. The other is only served as a hosted API.
Evaluation suite
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LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions)
