Kimi K3 In C
Kimi-k3-in-c is a lightweight, 2.78-trillion-parameter AI model that runs on a single CPU, allowing for portable and efficient inference without relying on GPUs or external frameworks.
- •When you need to deploy a large language model on a resource-constrained device or environment
- •When you want to avoid dependencies on external frameworks or libraries like BLAS
- •When you require a highly portable AI solution that can run on various platforms with minimal setup
To test the model's capabilities, you can use a prompt like `What are the implications of using a large language model like Kimi K3 in a resource-constrained environment?`
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/kimi-k3-in-c && curl -fsSL https://workflowstacks.com/api/skills/kimi-k3-in-c/claude-skill -o ~/.claude/skills/kimi-k3-in-c/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Kimi K3 In C is a large C project (~18k lines across 52 code files, plus 11 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit this month, Apache-2.0 license, has a test suite.
- 1README.mdStart here — what it does and how to install it
- 2pyproject.tomlDependencies and the commands it exposes
- 3src/cache/k3_cache.cInside src/ — the main logic begins here
- 4examples/01-hello.shA worked example — copy this to get going
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/kimi-k3-in-c && curl -fsSL https://workflowstacks.com/api/skills/kimi-k3-in-c/claude-skill -o ~/.claude/skills/kimi-k3-in-c/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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