PrismML: Ternary Bonsai 2 9B Rank
Ternary Bonsai 2 9B has an overall score of 67 out of 100, tied for rank 133 of 291. The published scores are price 92, context 53, parameters 24, and recency 99. The overall score is their average. freshness is not published and is left out of the average.
Data sourced from OpenRouter API and manual data collection | Last updated: Nov 3, 2026, 8:01 AM UTC
Component scores are ranked in
tied for rank 133 of 291
Component scores
| Score | Result | Published value | Source |
|---|---|---|---|
| Freshness | — | — | AI Knowledge Cutoff |
| Recency | 99 | AI Release Date | |
| Context | 53 | 262K tokens, output 65.5K | AI Context Window |
| Parameters | 24 | 9B total | AI Parameter Count |
| Price | 92 | $0.0925 / 1M blended, $0.08 / 1M input, $0.13 / 1M output | AI Token Price |
132 listed models have a higher overall score. Among PrismML models, it ranks 2 of 2.
Ternary Bonsai 2 9B is PrismML’s compact, open-weight language model for conversational AI, reasoning, and tool use. Built on Qwen3.5, it uses ternary weights packed into 2 bits for efficient...
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Frequently asked questions
What is the Ternary Bonsai 2 9B rank?
Ternary Bonsai 2 9B has an overall score of 67 out of 100, tied for rank 133 of 291. The published scores are price 92, context 53, parameters 24, and recency 99. The overall score is their average. freshness is not published and is left out of the average.
Where does Ternary Bonsai 2 9B rank?
Ternary Bonsai 2 9B is tied for rank 133 of 291. 132 listed models have a higher overall score. Among PrismML models, it ranks 2 of 2.
What scores make up Ternary Bonsai 2 9B?
Ternary Bonsai 2 9B scores price 92 (AI Token Price), context 53 (AI Context Window), parameters 24 (AI Parameter Count), and recency 99 (AI Release Date). The overall score of 67 is the average of those 4.