Discover production-ready fine-tunes, test them instantly in the browser, and deploy them to serverless API endpoints in one click.
3 steps. Discover, test, and deploy production-ready fine-tunes in minutes. #
Discover
Find highly specialized adapters for coding, customer support, data extraction, and more, all built by top creators.
Test
Stop guessing. Use our side-by-side Playground to instantly A/B test an adapter against its base model before you deploy.
Deploy
One click to push any adapter to a production-ready, serverless API endpoint. No GPU provisioning required.
Deploy endpoints at scale with zero cold starts #
Dynamic header-based routing matches incoming API requests to adapter registers. Weights swap dynamically inside warm GPU memory pools with sub-millisecond execution overhead, completely eliminating container cold starts.
Hot-swap LoRA adapters on a single base model. #
Click an adapter from the registry to route inference to that LoRA in real-time. One base Llama 3.1 8B instance serves 8 distinct personas dynamically with zero container restarts.
Build locally. Scale globally. #
The drop-in router for agentic workflows. AptAI acts as an OpenAI-compatible proxy. Point your existing frameworks (OpenHands, AutoGen, CrewAI, Aider) directly to your cloud endpoints or local CLI. Zero code rewrites required.
Get paid for your fine-tunes. #
Turn your specialized datasets and domain expertise into recurring revenue. AptAI provides the infrastructure to host, protect, and monetize your custom models. Set your own price per token and let thousands of developers route traffic to your endpoint.
70 / 30 Revenue Share
You keep 70% of all inference revenue generated by your adapter. We handle the billing and infrastructure.
Protect Your IP
We serve your adapter on managed endpoints. Your proprietary .safetensors weights are never exposed for public download.
Flexible Pricing
Set your own price per 1M tokens based on the complexity and value of your fine-tune.
Train in minutes. Serve in milliseconds.
Stop wrestling with complex infrastructure. AptAI utilizes state-of-the-art optimizations to make the entire model lifecycle seamless. By leveraging Unsloth-optimized kernels for rapid fine-tuning, and high-density multi-adapter serving (vLLM) on scalable serverless clusters, we deliver the performance of dedicated GPUs at a fraction of the cost.
| Infrastructure Metric | AptAI Serverless | Traditional Hosting |
|---|---|---|
| Fine-tuning speed | 2x-5x faster (Unsloth-optimized) | Hours to days |
| Adapter density | 100+ adapters per base model | 1 model per dedicated GPU | | GPU Memory Usage | Shared base VRAM (Dynamic swapping) | Duplicated base footprints | | Base hosting costs | Pay-per-inference | $150+ / mo per dedicated GPU |
Fine-Tuning Configuration #
Advanced mode: Explicit control over adapter matrices, learning rates, and target layers.
FAQ #
It's a marketplace of production-ready fine-tunes — small, focused model adapters that plug into a shared base model. Instead of hosting a full model per task, you register an adapter once and route requests to it instantly.
Adapters activate inside warm GPU memory pools with sub-millisecond overhead. Because the base model is always resident in VRAM, there is zero container initialization — the first request is just as fast as the hundredth.
Yes. One click pushes any registered adapter to a production-ready serverless API endpoint — OpenAI-compatible, with auto-scaled GPU capacity. No provisioning, no GPU setup.
Every token served through your adapter earns a per-request share, tracked on-chain and paid out automatically. Pricing tiers, royalties, and usage caps are fully yours to configure.
Yes. AptAI acts as an OpenAI-compatible proxy, so OpenHands, AutoGen, CrewAI, and Aider connect with zero code rewrites — just point them at your endpoint.