PrismML-Eng/Bonsai-demo

Bonsai Demo

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PrismML-Eng/Bonsai-demo has 3k+ stars and 350+ forks on GitHub, is written in Shell, and was last pushed on Oct 15, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 52 minutes ago
Added to GitGenius on August 13th, 2026
Created on March 25th, 2026
Open Issues & Pull Requests: 21 (+0)
GitHub issues: Enabled
Number of forks: 382
Total Stargazers: 3,400 (+0)
Total Subscribers: 32 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 15.5 hours
Mean response time: 3.3 days
90th percentile: 9.0 days
Tracked items: 89

Maintainer activity

1 person did triage or write work on this repository in the last 12 months.

Counts unlabeled, assigned, unassigned, milestoned, demilestoned, locked, unlocked over the last 12 months. These are issue and pull request events that require triage or write permission. Commits and code review are not counted. labeled and renamed are excluded because GitHub issue forms record the issue author as the actor. Figures from October 18, 2026. This count is not comparable across projects: each project's automation decides which of these events a person emits. How this is counted.

How this project is maintained

About 6% of issues opened in the past year have never received a reply. 83% of issues opened in the past year have been closed, leaving a working backlog. Three people close 93% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 16
New in 7 days: 4
Closed in 7 days: 0
Avg open age: 5 days
Stale 30+ days: 1
Stale 90+ days: 0

Recent activity

Opened in 7 days: 4
Closed in 7 days: 0
Comments in 7 days: 1
Events in 7 days: 1

Top labels

  • bug (1)

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Detailed Description

Bonsai Demo is a demonstration repository for running quantized language models locally across multiple platforms and hardware accelerators.

The project addresses the challenge of running capable language models on consumer hardware by providing ready-to-use implementations of Bonsai models, which use extreme quantization techniques to reduce model size while maintaining quality. Bonsai models employ 1-bit and ternary (roughly 1.7-bit) quantization schemes that pack weights into minimal storage, allowing models to run on devices from iPhones to standard laptops. The demo provides shell scripts to download models and launch a local inference server with a web interface, supporting Mac via Metal acceleration, Linux and Windows via CUDA, Vulkan, or ROCm, and CPU-only setups.

Developers should choose this tool if they need to run language models entirely locally without cloud dependencies and have limited hardware resources. The repository suits projects requiring vision capabilities, tool calling, or extended context windows, as the newest Bonsai 27B family adds vision-language support, native OpenAI-style tool calling, and reasoning models alongside the smaller quantized variants. The tool integrates with llama.cpp, with both 1-bit and ternary quantization formats landing in mainline llama.cpp, meaning models can eventually be used with standard llama.cpp tooling rather than remaining tied to this demo repository.

The project maintains active development with regular updates to support new model sizes and quantization formats. The repository includes detailed documentation for specific use cases, such as guides for AI coding agents and vision capabilities. Community benchmarking infrastructure is present, allowing users to contribute performance results across different hardware configurations. The codebase provides hardware-specific configuration options and defaults, indicating attention to making the tool accessible across diverse setups.