linne-oak 1.0 (31B) vs torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout)
As of Oct 14, 2026, linne-oak 1.0 (31B) leads torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout) in 1 of 1 shared categories: Decision models.
linne-oak 1.0 (31B)
Yes. SOTA in co-SOTA in Decision models.
torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout)
#35 Best current rank: #35 in Decision models, as of Oct 14, 2026.
| Category | linne-oak 1.0 (31B) | torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout) |
|---|---|---|
| Decision models | #1 · Co-SOTA · Decision models Margin 0 Jev Decision Index · Oct 14, 2026 | #35 · #35 in Decision models Margin 15.151515151515156 JevBench · Oct 8, 2026 |
linne-oak 1.0 (31B): price per 1M tokens is unset in the catalog.
torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout): price per 1M tokens is unset in the catalog.
linne-oak 1.0 (31B): open weights.
torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout): open weights.
Decision models: As of Oct 14, 2026, linne-oak 1.0 (31B) leads torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout) in Decision models at #1 against #35.
linne-oak 1.0 (31B) · torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout)
linne-oak 1.0 (31B) or torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout)?
As of Oct 14, 2026, linne-oak 1.0 (31B) leads torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout) in 1 of 1 shared categories: Decision models.
linne-oak 1.0 (31B) or torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout) for Decision models?
As of Oct 14, 2026, linne-oak 1.0 (31B) leads torchcast-decision-12b (Torchcast AI, Gemma-4-12B fine-tune, option-letter logprob readout) in Decision models at #1 against #35.