Ternary Bonsai 2 27B

Ternary Bonsai 2 27B ranks #113 out of 230 models on the public BenchAlign leaderboard, with a score of 50.78/100. Its evidence status is Estimated, and this profile shows 21 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Ternary Bonsai 2 27B ranks #78 out of 184 eligible models for knowledge and understanding, with a public category score of 50.6/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Ternary Bonsai 2 27B ranks #64 out of 154 eligible models for coding and programming, with a public category score of 49.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Ternary Bonsai 2 27B has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Ternary Bonsai 2 27B ranks #59 out of 154 eligible models for agentic tool use and computer tasks, with a public category score of 49.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Ternary Bonsai 2 27B has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Ternary Bonsai 2 27B ranks #64 out of 124 eligible models for instruction following, with a public category score of 71/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Ternary Bonsai 2 27B is an open-weight model from Prism ML. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

No. Ternary Bonsai 2 27B currently has 22 source-displayable rows across 446 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

Ternary Bonsai 2 27B has a documented context window of 262K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.