Getting started
Getting started
A weave sends your task to several models at once and returns one answer. This quickstart walks you from sign-up to your first run, then points you at the tutorials for the patterns worth learning next.
1. Create your account
Sign up with your email. The free plan needs no card and includes hourly runs on the free model set, so you can try real weaves before deciding anything.
2. Start a new weave
From your dashboard, click New Weave. A weave is one task run across several models at once. You write the prompt once, and LLMWeave sends it to each model and brings the answers back together.
3. Start from a template, or from scratch
Templates are ready-made recipes for working with several models (consensus draft, rank and fuse, best of N, debate and decide). Pick one to see how a good weave fits together, or start from scratch and choose the models yourself.
4. Run it and read the synthesis
Run the weave. You'll see the per-model work and then a single synthesized answer that merges the strongest parts. The estimate shows cost before you commit; the final cost is tracked per model.
5. Chain, share, or export
Continue the conversation to refine the result, share a public link, or export the output. From here, the tutorials cover the patterns that make multi-model worth it.
Next: learn the patterns
Compare Claude, GPT, and Gemini in one run
Send a single prompt to several frontier models at once and see their answers together, so you can judge accuracy, tone, and cost in one place.
BeginnerBuild a consensus draft that merges multiple models
Instead of picking one model’s answer, merge several into a single stronger draft. This is the pattern most people want when they say "use multiple models".
IntermediateRank and fuse multiple model outputs
Generate several candidate answers, rank them, and fuse the best parts into one result. Useful when quality matters more than speed.
IntermediateGround a weave in current sources with web search
Turn on web search so models answer from current sources rather than training memory. Essential for anything recent or fact-sensitive.
IntermediateSet up a multi-step workflow in The Loom
Chain multiple steps into a durable workflow that runs in the background and can pause for human review. This is where LLMWeave goes past a single prompt.