---
title: "Olla Integrations Overview - Supported Backends & Frontends"
description: "Complete overview of Olla's supported integrations. Backend support for Ollama, LM Studio, vLLM, OpenAI compatibility, and frontend integration with OpenWebUI."
keywords: ["olla integrations", "backend support", "ollama integration", "lm studio", "vllm", "openai compatibility", "openwebui"]
---

# Integrations

Olla supports various backends (endpoints) and front-ends integrations powered by Olla [Profiles](../concepts/profile-system.md).

## Backend Endpoints

Olla natively supports the following backends:

| Backend | Type | Description |
|---------|------|-------------|
| [Ollama](./backend/ollama.md) | `ollama` | Native support for [Ollama](https://github.com/ollama/ollama), including model unification |
| [LM Studio](./backend/lmstudio.md) | `lm-studio` | Native support for [LM Studio](https://lmstudio.ai/), including model unification |
| [llama.cpp](./backend/llamacpp.md) | `llamacpp` | Native support for [llama.cpp](https://github.com/ggml-org/llama.cpp) lightweight C++ inference server with GGUF models, including slot management, code infill, and CPU-first design for edge deployment |
| [LMDeploy](./backend/lmdeploy.md) | `lmdeploy` | Native support for [LMDeploy](https://github.com/InternLM/lmdeploy), InternLM's high-performance inference server with TurboMind C++/CUDA engine |
| [vLLM](./backend/vllm.md) | `vllm` | Native support for [vLLM](https://github.com/vllm-project/vllm), including model unification |
| [vLLM-MLX](./backend/vllm-mlx.md) | `vllm-mlx` | Native support for [vLLM-MLX](https://github.com/waybarrios/vllm-mlx), Apple Silicon inference using the MLX framework with native Anthropic Messages API |
| [SGLang](./backend/sglang.md) | `sglang` | Native support for [SGLang](https://github.com/sgl-project/sglang) with RadixAttention and Frontend Language, including model unification and vision support |
| [Lemonade SDK](./backend/lemonade.md) | `lemonade` | Native support for [Lemonade SDK](https://lemonade-server.ai/), AMD's local inference solution with Ryzen AI optimisation, including model unification |
| [LiteLLM](./backend/litellm.md) | `litellm` | Native support for [LiteLLM](https://github.com/BerriAI/litellm), providing unified gateway to 100+ LLM providers |
| [Docker Model Runner](./backend/docker-model-runner.md) | `docker-model-runner` | Native support for [Docker Model Runner](https://docs.docker.com/ai/model-runner/), Docker Desktop's built-in LLM inference server with multi-engine support (llama.cpp and vLLM), OCI model distribution, and native Anthropic Messages API |
| [oMLX](./backend/omlx.md) | `omlx` | Native support for [oMLX](https://github.com/jundot/omlx), a multi-model Apple Silicon (MLX) inference server managed from the macOS menu bar, with native Anthropic Messages API passthrough |
| [OpenAI Compatible](https://platform.openai.com/docs/overview) | `openai` | Generic support for any OpenAI-compatible API |

You can use the `type` in [Endpoint Configurations](/olla/configuration/overview/#endpoint-configuration) when adding new endpoints.

## Frontend Support

### OpenWebUI

Native support for [OpenWebUI](https://github.com/open-webui/open-webui) with Olla via:

* [OpenWebUI with Ollama](./frontend/openwebui.md)
* [OpenWebUI with OpenAI](./frontend/openwebui-openai.md)

### Claude-Compatible Clients

Olla provides Anthropic Messages API translation, enabling Claude-compatible clients to work with any OpenAI-compatible backend:

| Client | Description | Integration Guide |
|--------|-------------|-------------------|
| [Claude Code](./frontend/claude-code.md) | Anthropic's official CLI coding assistant | Full Anthropic API support |
| [OpenCode](./frontend/opencode.md) | Open-source AI coding assistant (SST fork) | OpenAI or Anthropic API |
| [Crush CLI](./frontend/crush-cli.md) | Modern terminal AI assistant by Charmbracelet | Dual OpenAI/Anthropic support |

These clients can use local models across any supported backend through Olla's Anthropic translation layer. Backends with native Anthropic support (Ollama, LM Studio, vLLM, vLLM-MLX, llama.cpp, Docker Model Runner, oMLX) use zero-overhead passthrough; the rest (SGLang, LMDeploy, Lemonade, LiteLLM, generic OpenAI-compatible) are served via translation.

### API Translation

Olla can translate between different LLM API formats:

| Translation | Status | Use Case |
|-------------|--------|----------|
| [Anthropic → OpenAI](./api-translation/anthropic.md) | ✅ Available | Use Claude Code with local models |

See [API Translation concept](../concepts/api-translation.md) for how this works.

## Profiles

[Profiles](../concepts/profile-system.md) provide an easy way to customise the behaviours of existing supported integrations (instead of writing Go code, compiling etc).

* You can customise existing behaviours
    * [Remove prefixes](../concepts/profile-system.md#routing-prefixes) you don't use
    * Add prefixes you would like to use instead    
* You can extend existing functionality
    * Add paths not supported to proxy through
    * Change the [model capability detection](../concepts/profile-system.md#capability-detection) patterns

You can also [create a custom profile](../concepts/profile-system.md#creating-custom-profiles) to add new capabilities or backend support until native support is added.