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.
FrontiersMind's decision model on a base it pre-trained from scratch. Each question reads the state and its own tokens once and a 256-dimension pointer head scores the options; Choice and Score take up to 255 entries, and nothing is generated.
Decides
choice, score, noul, classify, route
choice, score, noul
Architecture
intern-decision
lumma-fev
Fine-tuned from
qwen/qwen3.5-4b
frontiersmind/lumma-0.6b-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%
64.0%
Calibration error
—
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Valid action rate
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Median latency
44 ms
45.8 ms
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 lumma-fev?
intern-decision is from InternLM (Shanghai AI Laboratory) and lumma-fev from FrontiersMind. Both have open weights you can download and run. Both answer choice, score and noul questions. Only intern-decision answers classify and route. lumma-fev is the smaller model, at 649M parameters to 4.5B.
Which is more accurate, intern-decision or lumma-fev?
They report on different suites — intern-decision 80.6% on LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions), lumma-fev 64.0% on typed-decisions (maker's table; split not stated) — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, intern-decision or lumma-fev?
intern-decision: Free (open weights). lumma-fev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Which is faster, intern-decision or lumma-fev?
By their publishers’ figures, intern-decision answers in about 44 ms at the median and lumma-fev in about 45.8 ms — measured on different hardware, so treat it as a rough guide.
Can I run intern-decision or lumma-fev locally?
Yes, both: systemone pull internlm/intern-decision and systemone pull frontiersmind/lumma-fev download the weights.
Evaluation suite
LocalLLaMA/typed-decisions test split (400 cases, 2,000 decisions)
