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.
An open family of System One models. A LoRA adapter plus a pointer head on a frozen Qwen base returns a distribution per typed question in one forward pass, serves TypeSafe's /v1/systemone contract, and ships a fitted temperature with every checkpoint.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
intern-decision
kev
Fine-tuned from
qwen/qwen3.5-4b
qwen/qwen3.5-4b-base
License
apache-2.0
apache-2.0
Availability
Open weights
Open weights
Hosted by
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Input price
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Decision accuracy
80.6%
83.8%
Calibration error
—
0.042
Valid action rate
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Median latency
44 ms
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p95 latency
44.6 ms
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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 intern-decision and kev?
intern-decision is from InternLM (Shanghai AI Laboratory) and kev from Jared Palmer. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. kev is the smaller model, at 4.0B parameters to 4.5B.
Which is more accurate, intern-decision or kev?
They report on different suites — intern-decision 80.6% on LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), kev 83.8% on transfer-v4 (locked, out of domain) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, intern-decision or kev?
intern-decision: Free (open weights). kev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run intern-decision or kev locally?
Yes, both: systemone pull internlm/intern-decision and systemone pull jared-palmer/kev download the weights.
Evaluation suite
LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions)
