Uni Trainer pricing guide details
Pricing Overview
Uni Trainer follows an enterprise pricing model with a free entry point at $0.00 and custom pricing available on request for larger organizations. The platform is a local-first desktop application purpose-built for building datasets, fine-tuning LLMs, training computer vision models, and deploying AI pipelines to production -- all without writing code. The core product is available as a free download from the official website, giving teams full access to local GPU acceleration, LoRA/QLoRA fine-tuning, visual pipeline building, and SHA-256 provenance tracking from day one. There is no trial period, no credit card requirement, and no artificial feature gating on the free tier. This two-tier structure lets individual developers and small teams run real AI training workflows at zero cost while larger organizations secure terms that match their scale, compliance needs, and support requirements.
Plan Comparison
Uni Trainer splits its offering into two distinct access levels: the free tier and enterprise arrangements. The free tier is not a limited demo -- it ships the complete training toolkit.
| Feature | Free Tier | Enterprise (Contact Sales) |
|---|---|---|
| Local GPU Acceleration | Included | Included |
| LoRA/QLoRA Fine-Tuning for LLMs | Included | Included |
| Computer Vision Dataset Detection | Included | Included |
| Tabular ML with Auto Feature Handling | Included | Included |
| Small Language Model (SLM) Workflows | Included | Included |
| Visual Pipeline Builder | Included | Included |
| SHA-256 Provenance Tracking | Included | Included |
| Data-to-Deploy Pipeline | Included | Included |
| Priority Support | Not included | Included |
| Custom Integrations | Not included | Included |
| Deployment Assistance | Not included | Included |
| SLA Guarantees | Not included | Included |
| Dedicated Account Manager | Not included | Included |
Every core capability ships in the free download. Local GPU acceleration handles the compute layer. LoRA and QLoRA fine-tuning cover LLM adaptation without full model retraining. Automatic dataset structure detection simplifies computer vision project setup, and the tabular ML module handles feature and target selection automatically. The visual pipeline builder replaces the Jupyter and CLI workflows that typically slow down AI development.
There are no per-seat fees or usage caps on the free tier. Teams can evaluate every feature at production scale before committing to an enterprise contract, which removes the risk of paying for capabilities that do not fit the workflow.
Hidden Costs and Considerations
While the software itself starts at $0.00, teams should budget for hardware. Local GPU acceleration requires a capable NVIDIA GPU, and training large language models demands significant VRAM -- 16 GB or more for substantial LoRA fine-tuning jobs. Data storage for datasets and model checkpoints can grow quickly during active fine-tuning workflows, so adequate SSD capacity matters. Organizations moving to enterprise plans should factor in onboarding time for custom integrations. There are no documented overage charges, metered API fees, or token-based billing since all computation runs locally on your own hardware.
How Uni Trainer Pricing Compares
Uni Trainer takes a fundamentally different approach from most AI platforms by running entirely on local hardware. This eliminates the recurring compute costs that cloud-based competitors charge, but it shifts the cost burden to upfront hardware investment.
| Tool | Pricing Model | Starting Price | Entry Tier Details |
|---|---|---|---|
| Uni Trainer | Enterprise | $0.00 | Free local desktop app, full features |
| Fusedash | Usage-Based | $0.00 | Free tier, then $5/$15/$25 token packs |
| HypeScribe | Paid | — | Starter with 30 transcriptions/mo |
| Anthropic | Freemium | $0.00 | Free tier, Pro at $20/mo, Team at $25/user/mo |
Fusedash starts free but transitions to usage-based token packs at $5, $15, and $25 as consumption grows, meaning costs scale directly with workload volume. HypeScribe offers a Starter plan with 30 transcriptions, Pro with 60 transcriptions and a 10-meeting limit, and Ultra with 300 transcriptions and a 30-meeting limit. Anthropic offers a free tier, then steps up to $20/mo for Pro and $25/user/mo for Team plans, with Enterprise pricing available on request.
Uni Trainer stands apart because the free tier includes the complete feature set with no usage limits and no cloud dependency. The trade-off is clear: you supply your own GPU hardware rather than paying for cloud compute. For teams that already own capable hardware, this model delivers the lowest total cost of ownership. For teams without GPUs, the upfront hardware purchase must be weighed against the monthly subscription fees that cloud alternatives charge over time. Teams running frequent training jobs will recoup hardware costs faster than those with sporadic workloads, so the break-even calculation depends heavily on training volume and model complexity.