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HEAD TO HEAD
Ruoxi Qiu: canopy-jev and FrontiersMind: lumma-fev, compared on what they decide, where they run, what they cost and what their publishers report.
| Property | camellia86/canopy-jev | frontiersmind/lumma-fev |
|---|---|---|
| Summary | Ruoxi Qiu's decision adapter for a frozen Qwen3.8-27B: a 6.3M-parameter LoRA on the last four text layers plus a numerical prior. One shared state feeds isolated question branches; each Choice, Noul or Score question returns probabilities with no generated tokens. | 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, noul, score | choice, score, noul |
| Architecture | canopy-jev | lumma-fev |
| Fine-tuned from | qwen/qwen3.8-27b | frontiersmind/lumma-0.6b-base |
| License | apache-2.0 | apache-2.0 |
| Availability | Open weights | Open weights |
| Hosted by | — | — |
| Input price | — | — |
| Decision accuracy | 87.4% | 64.0% |
| Calibration error | — | — |
| Valid action rate | — | — |
| Median latency | — | 45.8 ms |
| p95 latency | — | — |
| Evaluation suite | JevBench public set (231 items; 202 correct), the maker's own fresh zero-shot run with the upstream scorer | typed-decisions (maker's table; split not stated) |
| Latest version | 0.1.0 | 2026.09 |
| Variants | LICENSE, NOTICE, artifacts, licenses | LICENSE, NOTICE |
| Size of latest version | 24.1 MB | 1.2 GB |
| Files | 11 | 12 |
| Downloads | 0 | 1 |
| Stars | 0 | 0 |
| Tags | system-one, qwen, lora, adapter, shared-state, 27b | system-one, pointer-head, multilingual, indic, 649m |
| Updated | Oct 7, 2026 | Oct 7, 2026 |
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.
canopy-jev is from Ruoxi Qiu and lumma-fev from FrontiersMind. Both have open weights you can download and run. Both answer choice, noul and score questions. lumma-fev is the smaller model, at 649M parameters to 27B.
They report on different suites — canopy-jev 87.4% on JevBench public set (231 items; 202 correct), the maker's own fresh zero-shot run with the upstream scorer, 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.
canopy-jev: Free (open weights). lumma-fev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Yes, both: systemone pull camellia86/canopy-jev and systemone pull frontiersmind/lumma-fev download the weights.