Local-first model evaluation for developers

Evalvo helps developers compare local models before they spend money on APIs or commit a model to production.

Choosing a model should not be guesswork. Evalvo gives developers a local-first way to run the same prompt across downloaded models and paid providers, then compare each response against the output they expected.

Start with the models already on your machine, add API keys only when a stronger baseline is useful, and decide with evidence before you wire a model into production.

Local-first

Start with models you run yourself.

API-ready

Compare paid providers when you need a baseline.

Model arena

Run the same prompt across selected models.

Expected outputs

Score responses against the result you need.

Why Evalvo exists

Developers should be able to test local models before defaulting to paid AI APIs. Evalvo is built for the moment when you have a real prompt, a few candidate models, and a production decision to make.

You can download local models, run them against the same tasks, compare the outputs, and decide whether a model on your machine is good enough or whether a paid provider is worth the cost.

Evalvo is built by Šimon Ochotnický, a solo developer focused on making model evaluation practical, repeatable, and transparent.

Evalvo brings the evaluation workflow into one place: choose the models, write the prompt, define what a good answer should look like, and compare the responses side by side.

The goal is simple: help developers choose based on evidence instead of hype, benchmarks, or guesswork. Local-first evaluation keeps experimentation close to the machine while still leaving room to compare API models when they matter.

Built and backed by

Šimon Ochotnický

Founder and solo developer