Everyone who self-hosts models has asked the same question in a different costume: what can this machine actually run? LLMFit answers it directly. Point it at your hardware and it lists every model that fits, ranked by how well it fits, with links to download the exact file.
From guessing to knowing
The usual way to pick a local model is folklore: a Reddit comment, a half-remembered benchmark, a VRAM table on a wiki. LLMFit replaces that with a scan. It reads your GPU, memory, and CPU, then matches them against the model catalog so you stop downloading files your hardware was never going to enjoy.
The best model is not the biggest one. It is the biggest one your machine runs well.
What it shows
For each model, LLMFit tells you whether it fits, how comfortably, and at which quantization. That turns the Q4-versus-Q8 debate into a concrete answer for your specific box instead of an average answer for someone else’s.
Before LLMFit
Guess a size, download gigabytes, watch it crawl, delete, repeat.
After LLMFit
See every capable model for your hardware up front, pick the best fit, download once.
Where it sits in the stack
LLMFit is the step before the runtime. Run it first, then hand the winning file to Ollama, LM Studio, or llama.cpp. It pairs naturally with the model cards on Hugging Face: the card tells you what the model is, LLMFit tells you whether it is for you.
Try it: the source and downloads live at github.com/AlexsJones/llmfit. One scan replaces an afternoon of trial and error.