Model overview
Ternary (INT2) `.litertlm` bundles of `prism-ml/Ternary-Bonsai-1.7B-unpacked`, packaged for the LiteRT-LM runtime and Google AI Edge Gallery. > **Recommended: `bonsai-1.7b-int2pc-4k-gpu.litertlm`.** The plain, unmodified build with > no optimizations applied. Everything else in this repo is **experimental** — longer > context or lighter activations, but whether a given one loads depends on your app's > LiteRT / LiteRT-LM version and dependencies. Start with the recommended build; reach for > an experimental one only if you specifically need what it offers. `32768` is the model's full context — `max_position_embeddings` for Ternary-Bonsai-1.7B is 32768, so the long-context builds here sit at the ceiling rather than truncating it.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。