OpenAI-compatible
Drop-in replacement — change the base URL, keep your code
AI & MLFrom $99/app/month
Managed LocalAI Hosting
OpenAI-compatible local AI inference API
What is LocalAI on ManageStacks?
LocalAI is a drop-in OpenAI API replacement for running LLMs, image generation, and audio models locally. ManageStacks deploys LocalAI with GPU acceleration and optimized model storage.
LocalAI is a drop-in OpenAI API replacement for running LLMs, image generation, and audio models locally. ManageStacks deploys LocalAI with GPU acceleration and optimized model storage.
Last updated Official siteSource on GitHubDocumentation
About LocalAI
What LocalAI does, and why teams deploy it.
LocalAI is a free, open-source alternative to OpenAI that acts as a drop-in replacement REST API compatible with the OpenAI API specification. It runs LLMs, generates images, creates audio transcriptions, and produces embeddings entirely on local hardware without requiring a GPU, though GPU acceleration is fully supported.
LocalAI supports a broad range of model families including LLaMA, Mistral, Stable Diffusion, and Whisper. It provides a single API endpoint that mimics the OpenAI interface, making it straightforward to migrate existing applications from cloud AI services to self-hosted inference.
DIY vs ManageStacks
What running LocalAI yourself looks like — and what it looks like with us.
DIY self-hosting
- Install CUDA drivers, cuDNN, and container runtimes on GPU VMs by hand
- Download and convert model weights between GGUF, safetensors, and GGML formats manually
- Write wrapper APIs to mimic the OpenAI format for each model backend
- Monitor GPU memory, inference latency, and model loading without built-in tooling
- Handle model versioning and storage across multiple servers with custom scripts
On ManageStacks
- Subscribe through your AWS, Azure, or GCP marketplace
- LocalAI deploys with GPU drivers, CUDA, and persistent model storage pre-configured
- OpenAI-compatible API works out of the box — change the base URL and go
- Model gallery for one-click downloads of LLaMA, Mistral, Stable Diffusion, Whisper, and more
- Monitoring dashboards track GPU utilization, inference latency, and model load times
LocalAI on ManageStacks — key numbers
GPU + CPU
CUDA-accelerated inference with CPU fallback for smaller models
Multi-modal
LLMs, image generation, embeddings, and audio in one API
50+ models
LLaMA, Mistral, Phi, Stable Diffusion, Whisper, and more via gallery
Key features
Everything LocalAI ships with, running on our stack.
- OpenAI-compatible REST API for drop-in replacement
- Support for LLMs, image generation, and audio models
- CPU and GPU inference with automatic optimization
- Model gallery for one-click model downloads
- Text embeddings and vector generation
- Function calling and grammar-constrained output
How it deploys
From subscribe to live in minutes.
Subscribe
Subscribe to ManageStacks through your AWS, Azure, or GCP marketplace.
Provision
LocalAI instance spins up with GPU drivers, CUDA toolkit, and persistent model storage — typically 5-8 minutes for GPU instances.
Load models
Download models from the built-in gallery or upload custom GGUF/safetensors files. Models persist across restarts.
Serve inference
Point your applications at the OpenAI-compatible endpoint. Supports chat completions, embeddings, image generation, and audio transcription.
Who this is for
Built for teams that want LocalAI to just work.
Teams moving inference off cloud APIs
Your LLM API bill is growing and you want to run Mistral, LLaMA, or Phi locally. LocalAI gives you OpenAI-compatible inference on your own GPU without rewriting application code.
Privacy-first AI deployments
User queries, documents, and embeddings cannot leave your infrastructure. LocalAI on ManageStacks keeps all inference local to your cloud region with no external API calls.
Multi-modal AI applications
You need text generation, image creation, embeddings, and audio transcription from a single API. LocalAI consolidates all of these behind one OpenAI-compatible endpoint.
Compliance & compatibility
What we handle, what LocalAI runs on.
Compliance & operations
- All inference runs locally — no data leaves your cloud region
- TLS-encrypted API endpoint
- GDPR and HIPAA-compatible — zero third-party data transmission
- Model weights stored on encrypted persistent volumes
- OS-level and CUDA security patches applied during your maintenance window
Compatibility
- Version
- Latest LocalAI stable (validated with CUDA driver compatibility before upgrade)
- Runtime
- Go + C++ backends on containerized infrastructure with NVIDIA CUDA 12.x
- Dependencies
- NVIDIA GPU drivers, persistent storage for model weights
- Min. resources
- 4 vCPU / 16 GB RAM / 1x NVIDIA T4 or better (GPU); 2 vCPU / 8 GB RAM (CPU-only)
How ManageStacks helps
We handle the parts you shouldn't be writing yourself.
ManageStacks deploys LocalAI with pre-configured GPU drivers, persistent model storage, and monitoring dashboards. Run a private OpenAI-compatible API without managing CUDA dependencies or container orchestration.
How it compares
LocalAI on ManageStacks vs the alternatives.
How LocalAI on ManageStacks compares to other self-hosted and managed inference platforms.
| Property | LocalAI on ManageStacksUs | Ollama | vLLM | AWS Bedrock |
|---|---|---|---|---|
| Deployment | Managed on your AWS, Azure, or GCP | Self-hosted (you manage) | Self-hosted (you manage) | AWS-managed |
| Data residency | Your cloud region | Your infrastructure | Your infrastructure | AWS region |
| Pricing basis | Flat per instance | Your compute cost | Your compute cost | Per token |
| API compatibility | OpenAI-compatible | Ollama API (partial OpenAI compat) | OpenAI-compatible | AWS SDK (not OpenAI-compatible) |
| Multi-modal | Yes (LLM, image, audio, embeddings) | LLM + embeddings only | LLM only | Yes |
| Open source | Yes (MIT) | Yes (MIT) | Yes (Apache 2.0) | No (proprietary) |
Comparison focuses on architectural properties (deployment model, pricing basis, open-source status) that don't change with vendor pricing pages. Verify current pricing on each vendor's own site.
FAQ
Common questions about LocalAI on ManageStacks.
Can I use LocalAI as a drop-in replacement for OpenAI on ManageStacks?
Yes. LocalAI exposes an OpenAI-compatible API, so you can point any application that uses the OpenAI SDK to your ManageStacks-hosted LocalAI endpoint by changing the base URL.
Does ManageStacks provide GPU support for LocalAI?
ManageStacks provisions LocalAI on GPU-enabled infrastructure with CUDA drivers pre-installed. CPU-only deployments are also available for embedding and smaller model workloads.
How do I add new models to LocalAI on ManageStacks?
You can download models from the built-in model gallery via the API, or upload custom GGUF and safetensors files to the persistent model storage that ManageStacks provisions.
Deploy LocalAI in under 5 minutes.
Subscribe through your AWS, Azure, or GCP marketplace. We handle provisioning, SSL, monitoring, backups, updates, and security. From $99/app/month.