Frontier quality, on your task
Fine-tuned on your examples, a small open model matches or beats models many times its size, on the one task that matters to you.
Low-code fine-tuning for LLMs
Small models,frontier results.
The end-to-end platform for small language models. Tuned to your task, a small open model matches frontier accuracy at a fraction of the cost. Own your intelligence: private, compatible, no lock-in. Ever.
No credit card · pay only for GPU minutes you use$0.03 / GPU·min flat
- Bring data your way: CSV import, API, or the built-in chat editor
- OpenAI-compatible API: swap one base URL and keep your code
- Weights are yours to download anytime. No lock-in.
From raw data to serving API
One managed pipeline. You bring examples; we handle GPUs, training and serving.
Your dataCSV · API · UI
→- DatasetsUpload CSV, push via API, or write examples in the editor
- Fine-tuneOne-click training on small open models
- EvaluateLive loss curves and checkpoints while it trains
- ServeHosted inference in our cloud, or download the weights
Managed GPU infrastructure · $0.03 per GPU minute · stop anytime
PredictionsREST API · OpenAI-compatible
// do the math
Estimate your savings
Compare what you pay a big-model API today against a small model tuned to the same task, served on our GPUs.
Use case
Commercial API today
Estimated cost
Unavailable
Commercial API today
Your tuned small model on ReOpenly
saved per year at this volume
Assumes one always-on GPU at the rate above serving a tuned small open model at the selected use case. Training itself is separate and one-off. Scale-to-zero, bursty traffic or a bigger model change the math; this is the list-price estimate. 8/3/2026.
// small beats big
A small model tuned to your task beats a giant generalist
Case-based research on fine-tuned open models keeps finding the same result: you do not need a bigger model. You need a model that knows your data.
~1/10 the cost per answer
Fewer parameters need a fraction of the GPU. One rented replica serves a steady stream of requests for a flat per-minute rate, instead of a per-token bill that grows with every answer.
Milliseconds, not seconds
A tuned small model decodes at about 25 ms per token on our production hardware, so a short answer is back before a big model has finished thinking about it.
Why teams pick ReOpenly
Keep the code you already wrote
Point your OpenAI SDK at a new base URL and you’re done. Works with LangChain, n8n and friends.
const baseURL = "https://reopenly.com/api/projects/me/proj/openai/v1";
const client = new OpenAI({ baseURL, apiKey: "roy_..." });Your traffic becomes training data
Opt in to auto-save a share of inference requests to your dataset, curate them, and fine-tune. Your data only ever trains models you own.
Leave whenever you like
Every fine-tuned model can be downloaded anytime. Serve with us because it’s easy, not because you must.
Pricing you can read in one line
$0.03 per GPU minute, training or inference. 1 credit = $1. That is the whole pricing page.
$0.03 / GPU minute
Training or inference, same flat rate. Paid inference has a one-second minimum.
10 free credits
Every new account starts with 10 credits, enough for several fine-tunes on small models.
1 credit = $1. No tiers, no seats, no hidden fees.
Estimate your cost →Your first fine-tune is on us.
From CSV to a deployed, OpenAI-compatible endpoint in under an hour.
No credit card · weights yours to download