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.
Frontier Infra's open decision model. A LoRA merged into Qwen3.8-27B (thinking off) that answers one typed question per forward pass with a probability over the option labels, served through AINode's TypeSafe-compatible /v1/systemone.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
intern-decision
jebadiah
Fine-tuned from
qwen/qwen3.5-4b
qwen/qwen3.8-27b
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%
86.6%
Calibration error
—
0.113
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 jebadiah?
intern-decision is from InternLM (Shanghai AI Laboratory) and jebadiah from Frontier Infra. Both have open weights you can download and run. Both answer choice, score, noul, classify and route questions. intern-decision is the smaller model, at 4.5B parameters to 27B.
Which is more accurate, intern-decision or jebadiah?
They report on different suites — intern-decision 80.6% on LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), jebadiah 86.6% on JevBench public set (231 items), maker's run with the v1.4.2 harness; ECE on the hard tier — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, intern-decision or jebadiah?
intern-decision: Free (open weights). jebadiah: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run intern-decision or jebadiah locally?
Yes, both: systemone pull internlm/intern-decision and systemone pull frontier-infra/jebadiah download the weights.
Evaluation suite
LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions)
JevBench public set (231 items), maker's run with the v1.4.2 harness; ECE on the hard tier
