AlexsJones

AlexsJones / llmfit

Public

Hundreds of models & providers. One command to find what runs on your hardware.

llm localai skill
9,525
531
100% credibility
Found Feb 17, 2026 at 445 stars 22x -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Rust
AI Summary

A terminal application that detects your computer's hardware capabilities and ranks large language models by compatibility, speed, and quality for local running.

How It Works

1
🔍 Discover llmfit

You hear about a simple tool that checks your computer's power and suggests the best AI helpers that will run smoothly on it.

2
📥 Get the tool

Download and set it up on your computer in moments with an easy one-step grab.

3
🚀 Launch and see your setup

Open the tool and instantly view a clear picture of your computer's memory, processor speed, and graphics strength at the top.

4
📋 Browse AI options

Scroll through a list of smart AI models ranked by how well they match your machine, with scores for speed, quality, and fit.

5
🔧 Narrow it down

Search by name, filter by perfect fits or categories like coding or chat, and toggle providers to focus on what you need.

6
⭐ Spot top picks

Highlight the best matches with green checks, estimated speeds, and memory use so you know exactly what will work great.

✅ Run your ideal AI

Pick a recommended model, download it elsewhere, and enjoy fast, capable AI thinking right on your own computer without slowdowns.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 445 to 9,525 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is llmfit?

llmfit is a Rust CLI tool that scans your hardware—RAM, CPU cores, GPU VRAM—and ranks 94 models from 30 providers like Meta Llama, Mistral, DeepSeek, and Qwen to find what actually runs smoothly. Run one command like `llmfit` for an interactive TUI table sorted by composite score across quality, speed, fit, and context, or `llmfit recommend --json` for scriptable output. It solves the guesswork of picking llm providers and models that fit your machine, handling MoE architectures, dynamic quantization, and multi-GPU setups without downloading anything.

Why is it gaining traction?

Unlike hands-on benchmarkers like llm-checker that require Ollama installs and real runs, llmfit delivers instant estimates via hardware probes and backend detection (CUDA, Metal, ROCm). Developers dig the TUI for quick filtering by fit level or provider, plus CLI flags for perfect fits, searches, or use-case recs like coding or embeddings. It stands out by supporting free ai models providers, small language models providers, and even github models deepseek, with JSON for agents and rate-limits-aware scripting.

Who should use this?

Hardware-limited devs running local inference on laptops or home servers, especially those evaluating embedding models providers or large language models providers before Ollama/vLLM pulls. AI tinkerers filtering by use case—coding with Qwen-Coder, reasoning with DeepSeek-R1—or comparing github models claude alternatives without cloud service models providers pricing. Teams scripting model selection via `llmfit fit --perfect` to avoid trial-and-error crashes.

Verdict

Grab it via `cargo install llmfit` if you run local LLMs—solid docs and TUI make it instantly useful despite 283 stars and 1.0% credibility score signaling early maturity. Low test coverage means watch for edge cases on exotic hardware, but it's a smart first pass before benchmarks.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.