Serverless, pay-as-you-train fine-tuning with total control. No setup, no bottlenecks, and no compromise on performance.
Keep full visibility on your fine-tuning workflows with easy job tracking, dataset management, and clear result visualisation.
![“A dark grid showcasing AI models categorized by their functionality. Top row: ‘Text Generation’ with ‘LLAMA 3.2 11B Instruct’ by Meta, ‘LLAMA 3 70B Instruct’ by Meta, and ‘Mixtral 8x22B Instruct’ by Mistral AI. Bottom row: ‘Text Generation’ with ‘AMD LLAMA 135M’ by AMD, ‘Text-to-Image’ with ‘Stable Diffusion 3 Medium’ by Stability AI, and ‘Text-to-Image’ with ‘Flux.1 [Schnell]’ by Black Forest Labs.”](https://cdn.prod.website-files.com/666078e26595dfe9b1e8171f/6737719462cb3cb2d0e304b7_severless-feature-1.avif)
No, we built Nscale Fine-tuning to be simple and accessible, only exposing more advanced settings and parameters if you need them. This service does not require machine learning or infrastructure management and can be started by any developer with $2 credit.
If a job fails or is cancelled, you're only billed for the tokens that were processed up to that point—no full-job charges or hidden costs. You’ll see a detailed breakdown in your job history, including how far the run got and how many tokens were used. You can clone or resume the job at any time to pick up where you left off.
Yes, each organisation has isolated cloud storage. Data will not be shared with any other organisation or the model providers.
Yes, providing you have enough credit, you can start multiple jobs. These jobs will be added to the queue and will start running once there is available resources.
