A 0.4B decision model made from the first 20 layers of Qwen3-0.6B plus a small attention head that compares options. It answers choice, noul and score questions in one pass, and choice order cannot change its answer by construction. Non-commercial licence.
A 396M ModernBERT-large cross-encoder that answers typed questions about a text or a JSON state: one or several options, scores, yes/no with "not stated", spans with evidence quotes, rankings and numeric bins, each with a confidence and an act-or-escalate signal.
Decides
choice, score, noul
choice, score, noul, rank, extract
Architecture
bev-decider
solvi
Fine-tuned from
qwen/qwen3-0.6b
answerdotai/modernbert-large
License
cc-by-nc-4.0
apache-2.0
Availability
Open weights
Open weights
Hosted by
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Input price
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Decision accuracy
74.7%
59.4%
Calibration error
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0.210
Valid action rate
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Median latency
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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 bev-decider and solvi?
bev-decider is from Avishek Biswas and solvi from solvi. Both have open weights you can download and run. Both answer choice, score and noul questions. Only solvi answers rank and extract. bev-decider reads up to 2K tokens of state, against 512 tokens for solvi. solvi is the smaller model, at 396M parameters to 478M. bev-decider is licensed cc-by-nc-4.0; solvi, apache-2.0.
Which is more accurate, bev-decider or solvi?
They report on different suites — bev-decider 74.7% on avbiswas/bev-decision test split (5,000 held-out questions over 2,617 states), the maker's own, solvi 59.4% on Fast Decisions public dev split (100 rows x 17 domains, macro), the maker's own harness, zero-shot — so the numbers do not rank them. Test both on your own labelled examples.
Which is cheaper, bev-decider or solvi?
bev-decider: Free (open weights). solvi: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run bev-decider or solvi locally?
Yes, both: systemone pull avishek-biswas/bev-decider and systemone pull solvi-ai/solvi download the weights.
Evaluation suite
avbiswas/bev-decision test split (5,000 held-out questions over 2,617 states), the maker's own
Fast Decisions public dev split (100 rows x 17 domains, macro), the maker's own harness, zero-shot
