MODEL PROFILE

Bonsai-4B-gguf

prism-ml · Bonsai-4B-gguf

Prism ML Website  |  Whitepaper  |  Demo & Examples  |  Colab Notebook  |  Discord - Deployed footprint fits on virtually any device with a GPU - **End-to-end 1-bit weights** across embeddings, attention projections, MLP projections, and LM head - **GGUF Q1_0 (g128)** format for 1-bit packing of weights with shared scales for each group (group size 128). - **Cross-platform**: CUDA (RTX/datacenter), Metal (Mac), Swift (iPhone/iPad), Android - **MLX companion**: also available as MLX 1-bit g128 for native Apple Silicon inference - **Google Colab** — try Bonsai in your browser, no setup required - **Whitepaper** — for more details on Bonsai, check out our whitepaper - **Demo repo** — comprehensive examples for serving, benchmarking, and integrating Bonsai - **Discord** — join the community for support, discussion, and updates - **1-bit kernels**: llama.cpp fork (CUDA + Metal) · MLX fork (Apple Silicon) · mlx-swift fork (iOS/macOS) - **Locally AI** — we have partnered with Locally AI for iPhone support

Text generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/31 17:31:58
OVERVIEW

Model overview

Prism ML Website  |  Whitepaper  |  Demo & Examples  |  Colab Notebook  |  Discord - Deployed footprint fits on virtually any device with a GPU - **End-to-end 1-bit weights** across embeddings, attention projections, MLP projections, and LM head - **GGUF Q1_0 (g128)** format for 1-bit packing of weights with shared scales for each group (group size 128). - **Cross-platform**: CUDA (RTX/datacenter), Metal (Mac), Swift (iPhone/iPad), Android - **MLX companion**: also available as MLX 1-bit g128 for native Apple Silicon inference - **Google Colab** — try Bonsai in your browser, no setup required - **Whitepaper** — for more details on Bonsai, check out our whitepaper - **Demo repo** — comprehensive examples for serving, benchmarking, and integrating Bonsai - **Discord** — join the community for support, discussion, and updates - **1-bit kernels**: llama.cpp fork (CUDA + Metal) · MLX fork (Apple Silicon) · mlx-swift fork (iOS/macOS) - **Locally AI** — we have partnered with Locally AI for iPhone support

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.

PRICING & COST

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 / channelInputOutputBilling unitCollected at
No verified prices yet. Check the source channel.

Estimate monthly base token costs

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Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.

INDEPENDENT BENCHMARKS

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。

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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。