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Go Reference Go version Linux llama.cpp release

Kronk is a Go SDK and model server for hardware-accelerated local inference. It provides high-level Go APIs over native inference engines without requiring Python or a separate model-serving stack:

The Kronk model server exposes OpenAI-compatible APIs for Chat Completions, Responses, embeddings, reranking, and audio transcription, plus an Anthropic-compatible Messages API. It also includes a browser interface, model management, security, observability, and integrations with OpenWebUI, OpenCode, and Claude Code. Malina is currently SDK-only and is not integrated into the model server.

Visit kronkai.com or read the manual for complete documentation.

Quick Start

The recommended installation method on macOS and Linux is Homebrew:

brew install ardanlabs/kronk/kronk

kronk server start

The fully qualified formula name trusts only the Kronk formula, not every item in the ardanlabs/kronk tap.

You can also install the CLI with Go on a supported platform:

go install github.com/ardanlabs/kronk/cmd/kronk@latest

kronk server start

Open http://localhost:11435 to manage models and use the Browser UI. The first model or SDK example you run can download the compatible native libraries and model files automatically.

For container deployment, persistent storage, and production setup, see Container Quick Start.

SDK or Model Server

The model server is built on the same public SDKs available to Go applications.

Use the SDK when you need Use the model server when you need
Inference inside a Go process HTTP APIs for one or more clients
Direct control over model loading and lifetime OpenAI- and Anthropic-compatible APIs
No separate server process Browser-based model management and testing
Application-specific caching and concurrency Authentication, rate limiting, metrics, and tracing

The Kronk SDK supports text generation, streaming, reasoning, tool calls, vision, embeddings, reranking, concurrent processing, and incremental message caching. Bucky supports file transcription, translation, channel-separated diarization, and live streaming transcription. Experimental Malina supports text-to-image, image-to-image, Canny ControlNet conditioning, ADetailer face refinement, AnimateDiff video generation, Real-ESRGAN upscaling, single-checkpoint and multi-file diffusion pipelines, and Motion-JPEG encoding.

Platform Support

Hardware acceleration depends on the operating system, architecture, inference engine, and library bundle. Kronk downloads native libraries that are compatible with the installed release.

OS CPU architectures Available GPU backends
Linux amd64, arm64 CUDA and Vulkan; ROCm on amd64
macOS amd64, arm64 Metal on arm64
Windows amd64, arm64 CUDA, Vulkan, and ROCm on amd64; arm64 is CPU-only

Not every backend is available for every SDK or architecture. Use the CLI or SDK library manager as the source of truth for combinations supported by your installed version. See Installation and Quick Start for current requirements.

Project Status

Kronk follows the native engines it integrates, and upstream changes can require coordinated releases of Yzma, Bucky, Malina, and Kronk. Use each subsystem's downloader instead of mixing native libraries from unrelated releases; every Kronk release is bound to known-compatible library versions.

Warning

Malina is experimental. Its public API is subject to change, and it is not yet a Kronk model-server backend.

See Breaking Changes, the release history, and the open issues for current status.

Sometimes there are breaking changes to the family of ggml libraries that require an update to yzma, bucky, malina and/or Kronk. Always choose to use the downloader for each system to make sure you have a compatible version of the libraries. A working version of each library is bound to each release.

Here are some of the known compatible versions:

kronk yzma llama.cpp bucky whisper.cpp malina stable-diffusion.cpp
1.32.7-rc 8ddb005 b11037 v1.1.3 v1.9.4 v1.1.2 master-869-07a85c7
1.32.6 ece4890 b10896 v1.1.2 v1.9.3 v1.1.0 master-849-d04e895
1.32.5 v1.26.0 v0.4.0 v1.1.2 v1.9.3 v1.0.8 master-841-6b3edaa
1.32.4 6bd0208 b10785 v1.1.1 v1.9.3 v1.0.6 master-841-6b3edaa

Kronk 1.32.7-rc pins the llama.cpp manifest as b11037@sha256:a6970a03e30d1070a69ca61986f7339beb18874d55b179e2f81ba38d73f116c5. The manifest authenticates the platform-specific archives selected by the downloader, so the default installation verifies both the manifest and the downloaded libraries. Malina v1.1.2 pins stable-diffusion.cpp as master-869-07a85c7@sha256:b27f800a8178d75d2202d93d4b5a0c2310f4e37caaade6e768c6ce454a580f3d. Its native ABI is incompatible with the preceding master-859 build, so upgrade the Malina dependency and native library bundle together.

Documentation and Examples

Representative examples:

make example-question         # Ask a local language model a question.
make example-agent            # Run a small coding agent.
make example-vision           # Prompt a vision model with an image.
make example-bucky            # Transcribe an audio file with Bucky.
make example-bucky-stream-vad # Stream transcription with Silero VAD boundaries.
make example-malina           # Generate an image with experimental Malina.
make example-malina-controlnet # Generate an image with Canny edge conditioning.
make example-malina-adetailer  # Detect and refine faces in a portrait.
make example-malina-animatediff # Generate AnimateDiff frames and write an AVI.
make example-malina-s2v ARGS='...' # Animate a portrait from WAV speech with Wan2.2 S2V.
make example-malina-upscale    # Enlarge an image with Real-ESRGAN.

Examples download compatible libraries and catalog-backed models on their first run; Wan2.2 S2V takes explicit component paths. Browse the complete examples module for chat, Responses, embeddings, reranking, RAG, streaming transcription, image-to-image generation, ControlNet, ADetailer, AnimateDiff, Wan2.2 S2V, image upscaling, model pools, session stores, and lower-level yzma usage.

Community and Support

Use GitHub Issues for bugs, feature requests, and planned work. If you are interested in contributing or need help, email Bill Kennedy or Ardan Labs.

Owner Information

Name:     Bill Kennedy
Company:  Ardan Labs
Title:    Managing Partner
Email:    bill@ardanlabs.com
BlueSky:  https://bsky.app/profile/goinggo.net
LinkedIn: www.linkedin.com/in/william-kennedy-5b318778/
Twitter:  https://x.com/goinggodotnet

Travel Schedule

Come find me at any of these cities or events this year. I will be giving workshops and talks about Kronk.

Dates Event Location Comments
Jan 29th - 2nd AI Plumbers Fringe, FOSDEM Brussels, Belgium Talk
Mar 4th - 5th Ardan Connect São Paulo, Brazil Training
Apr 20th - 25th Gophercamp 2026 Brno, Czech Republic Training, Talk
Apr 27th - 29th AI Dev 26 San Francisco, USA Attendee
May 17th - 23rd GopherCon Singapore Singapore Training, Talk
Jun 8th - 12th Genetec Corporate Training Montreal, Canada Training
Jun 14th - 19th GopherCon EU Berlin, Germany Training, Talk
JULY Summer Vacation Huntsville, AL Rest
Aug 3rd - 6th GopherCon USA Seattle, Washington Training, Talk
Aug 11th - 13th GopherCon UK London, England Training, Talk
Sep 1st - 4th GopherCon LATAM Florianópolis, Brazil Training, Talk
Sep 5st - 8th Personal Travel Roanoke, VA Personal
Sep 17th - 20th Personal Travel Syracuse, NY Personal
Sep 21st - 24th Meetup NYC NYC, NY Talk
Oct 6th - 9th Crusoe Corporate Training San Francisco, USA Training
Oct 12th - 14th Optus Corporate Training Sydney, Australia Training
Oct 22nd - 23rd Meetup Austin Austin, TX Talk
Oct 27th - 28th Meetup Bostom Boston, MA Talk
Oct 31th - 4th GoLab (GopherCon Italy) Bologna, Italy Training, Talk
Nov 6th - 8th UM v ND Southbend, IN Game Day
Nov 9th - 11th Las Vegas, NV Training
DECEMBER Winter Vacation Miami, FL Rest

Copyright 2025-2026 Ardan Labs

About

Go With Your Own Intelligence! Use Go for hardware accelerated local inference with llama.cpp, whisper.cpp, and stable-diffusion.cpp directly integrated into your Go applications. Kronk provides a high-level API and production ready model server.

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