Fine-tune and serve open-weight models on your own cloud GPUs without managing ML infrastructure
Run AI models on your own hardware with automatic optimization and a single endpoint
Stage
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Founded
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Based in
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Pricing model
Freemium
Open source
Pricing
Free: $0 (1 training run per month, 1 model deployment, 1 member); Starter: $49/month (5 training runs per month, 5 model deployments, 1 member); Pro: $199/month (unlimited training runs, 1,000 model deployments, 10 included members, $30/month for each extra seat); Enterprise: custom pricing. Free i
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Key features
Train models with SFT, DPO, or RL using LoRA or QLoRA
Monitor training with real-time loss, time and cost tracking
Evaluate models by comparing base and tuned performance
Serve models as OpenAI-compatible API or wake-on-demand
Support for vision models including Gemma 4 and Qwen3.8
DPO preference learning from paired answers
Run budget-controlled experiments with hour and price limits
Download adapters as standard LoRA files or publish to Hugging Face
Automatic model loading from Hugging Face and other sources
Hardware-aware model optimization for VRAM and context length
OpenAI-compatible endpoint
Support for multiple inference engines
Single unified endpoint for all models and machines
Distributed compute across multiple machines
Built-in app catalog with chat UIs and RAG tools
Integration with cloud providers
What makes it different
No training scripts required; workflow runs in console, CLI or via AI agent
GPU costs billed by your provider with zero markup from Tensorant
Data stays in your own storage; Tensorant keeps only workflow records
Free plan covers complete workflow on one model from import to API
Models are downloadable and portable to other platforms
Tensorant
dotcore