Home/Inference & Serving/whatcanirun

whatcanirun

fiveoutofnine/whatcanirun

Find best models and run them locally

GitHub Website

GraphCanon updated Aug 13, 2026 · GitHub synced Aug 13, 2026

23views this month

245 stars22 forksLast push May 4, 2026 TypeScript MIT

Decision brief

whatcanirun is ideal for developers looking to easily discover and run AI models locally, particularly on Apple Silicon hardware, through TypeScript-based instructions.

Good fit when

Ideal if your development environment relies on Apple Silicon hardware as it offers optimized guidance for such setups.
Suitable when you need clear and concise TypeScript-related resources to understand how to deploy AI models locally.

Avoid when

Not recommended if your project primarily uses languages other than TypeScript, as the instructions might not align with alternative development environments.
Avoid using it when you specifically require support for cloud-based AI model deployment processes; this tool emphasizes local environment setups.

Observed Jul 17, 2026 · Source: enrich:decision_facts

whatcanirun alternatives Trust report

Verify the decision

Adoption

Package downloads where a registry match exists. GitHub stars (245) are secondary evidence.

npm downloads (30d): 142·npm downloads API·Aug 13, 2026

Maintenance and security

Full trust report

Maintenance: Slowing (100d since push); As of Aug 13, 2026
Provenance: Not a fork · Personal account; As of Aug 13, 2026
Security (OSV): No lockfile; As of Jul 15, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

npm install whatcanirun

npm

Similar tools

Same-category neighbours. No typed graph edges are catalogued for this tool yet.

llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

83k★

llmfit

Hardware-aware model recommendation tool

37k★

oumi

Easily fine-tune, evaluate and deploy open source LLMs/VLMs

9.4k★

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A resource for identifying suitable AI models and instructions on running them in local environments.

Capability facts

MCP server: No MCP server detected
Source: repo_scan · Aug 13, 2026
Languages: typescript, javascript
Source: github.language+package.json · Aug 13, 2026

README

Getting Started This project uses Bun and Turborepo.

For agents

This page has a .md twin and JSON over the API.

/tools/fiveoutofnine-whatcanirun.md GET /api/graphcanon/tools/fiveoutofnine-whatcanirun GET /api/graphcanon/graph?tool=fiveoutofnine-whatcanirun