Comparisons
Onrup against the alternatives.
How honest are these comparisons?
Every page names at least one scenario where the other product is the better choice, and the build fails if one does not. Every price comes from the vendor’s own pricing page with the date it was checked. Raw GPU marketplaces are excluded, because we are not one and the comparison would be misleading.
How to read a comparison page
Start with the verdict at the top, which states in one sentence when the other product is the better choice. If that sentence describes your situation, the rest of the page will not change your mind and you should go and use them.
Then read the differences table, which is where the substance is. Billing model, spend control, evaluation and weight portability are the four axes that actually separate products in this category — everything else tends to converge, and a comparison built on the converged features is a comparison designed to be won.
Prices are quoted per GPU-hour where the vendor publishes one, and left blank where they do not. Several of these platforms bill per token instead, which is a genuinely different shape rather than a worse one: token pricing is cheaper for light and spiky traffic and dearer at steady volume. The crossover is usually around an endpoint being busy a fifth of the time, and it is worth working out on your own numbers.
On-demand H100, per GPU-hour
The one figure enough vendors publish for a like-for-like comparison. Anyone who does not publish a comparable rate is absent from this table rather than estimated into it.
| Provider | H100 80GB / hr | Ratio | Checked |
|---|---|---|---|
| Onrup | $2.99 | — | 2026-08-06 |
| Modal | $3.95 | 1.3× | 2026-08-06 |
| Together AI | $5.49 | 1.8× | 2026-08-06 |
| Replicate | $5.49 | 1.8× | 2026-08-06 |
| Baseten | $6.50 | 2.2× | 2026-08-06 |
| Fireworks AI | $7 | 2.3× | 2026-08-06 |
Every comparison
Onrup vs Together AI
Managed fine-tuning platformA broad model API with fine-tuning attached, covering the widest catalogue of open-weight models of anyone in this set.
Onrup vs Fireworks AI
Managed fine-tuning platformInference, fine-tuning and evaluation behind one API, with fine-tuned adapters served at the same per-token rate as the base model.
Onrup vs Modal
Serverless GPU platformServerless compute for arbitrary Python, billed by the second. Not a fine-tuning product — a substrate you build one on.
Onrup vs Baseten
Serverless GPU platformModel deployment and serving with strong operational tooling, compliance posture and cold-start engineering.
Onrup vs Replicate
Serverless GPU platformA catalogue of community-published models behind one API, billed per second of compute, with fine-tuning on a subset.
Onrup vs OpenAI fine-tuning
Closed model APIFine-tuning of OpenAI’s own closed models, served only from OpenAI. The default first stop, and the thing most teams are trying to leave.
Onrup vs Hugging Face
Managed fine-tuning platformThe model hub itself, plus AutoTrain for training and Inference Endpoints for serving. The centre of gravity of the open-weight world.
Onrup vs Predibase
Managed fine-tuning platformA fine-tuning platform built around serving many LoRA adapters from a single GPU. Acquired — predibase.com now redirects to Rubrik.
Onrup vs OpenPipe
Managed fine-tuning platformCapture production traffic from a large model, then train a small one to replace it on that exact distribution.
Onrup vs AWS SageMaker
Hyperscaler ML platformThe full machine-learning platform on AWS. Enormously capable, correspondingly heavy, and priced per instance-hour.
Onrup vs Google Vertex AI
Hyperscaler ML platformGoogle Cloud’s machine-learning platform, with tuning for Gemini and for a set of open-weight models.
Onrup vs AWS Bedrock
Closed model APIA managed API over several model vendors, with custom-model fine-tuning and provisioned throughput inside AWS.
Onrup vs Anyscale
Serverless GPU platformManaged Ray. Distributed training and serving for teams that have outgrown a single machine.
Onrup vs Lamini
Managed fine-tuning platformEnterprise fine-tuning with a focus on factual accuracy and hallucination reduction, deployable on-premises.
Looking for something else?
If you are researching a field rather than making a head-to-head decision, the alternatives pages cover each vendor’s wider set of options, and the landscape page lays out the whole market with sources.
Last verified 6 August 2026. Every competitor figure links to the vendor page it came from.
Start with the free tier
A magic link creates your account, your tenant and your first API key. No card until you ask for compute.