---
title: "AI Model Providers"
source: https://docs.autohand.ai/integrations/ai-model-providers
---

# AI Model Providers

Connect Autohand to your preferred AI models. Use cloud APIs for maximum capability or run models locally for privacy and offline access.

Quick answer

## What is the Autohand AI model providers integration?

Autohand model-provider integrations connect the coding agent to hosted APIs or local inference runtimes. You can choose the provider and model explicitly, keep credentials outside source control, and change runtimes without changing the task workflow.

Status

Available; support varies by provider

Requires

Cloud provider credentials for hosted APIs, or a supported local runtime and model files.

Configure with

Choose a provider and model with the Autohand CLI, `/model`, or your Autohand configuration file, then set the credential or endpoint named in the provider guide.

Best for

Selecting inference by capability, deployment environment, privacy, or cost.

**Know before you start:** Model IDs, context limits, pricing, quotas, and regional access are provider-controlled and can change independently of Autohand.

## Overview

Autohand separates the CLI interface from the AI model provider. This means you can switch between different models and providers without changing how you work. Whether you prefer cloud-hosted models or local inference, Autohand adapts to your needs.

You have two main options:

-   **Cloud providers** - Access powerful models via API with no hardware requirements
-   **Local providers** - Run models on your own machine for privacy and offline use

## Cloud providers

Cloud providers offer access to the most capable models without requiring powerful hardware. Your prompts are sent to remote servers for processing.

[

### OpenRouter

Recommended

Access 200+ models from Anthropic, OpenAI, Google, and more through a single API. Automatic fallbacks and cost optimization included.

-   Claude, GPT-4, Gemini, Llama, and more
-   Single API key for all providers
-   Automatic model fallback
-   Pay-per-use pricing

](/docs/integrations/openrouter.html)[

### OpenAI

Direct access to GPT-4o, GPT-4 Turbo, and o1 reasoning models. The industry standard for AI development with excellent documentation.

-   GPT-4o, GPT-4 Turbo, o1 reasoning
-   128K context window
-   Function calling support
-   Vision capabilities

](/docs/integrations/openai.html)[

### AWS Bedrock

Enterprise

Run Autohand through Bedrock Converse or Bedrock's OpenAI-compatible endpoints. Designed for AWS credential chains, profiles, private endpoints, and model access controls.

-   Converse, Chat Completions, and Responses modes
-   AWS credentials, SSO profiles, IAM roles, or Bedrock API keys
-   Inference profiles and ARN model IDs
-   Regional and private VPC endpoints

](/docs/integrations/aws-bedrock.html)[

### DeepSeek

Direct access to DeepSeek V4 models through an OpenAI-compatible API. A strong choice for coding, reasoning, and cost-sensitive engineering workflows.

-   DeepSeek V4 Flash and V4 Pro
-   OpenAI-compatible chat completions
-   Fast coding and reasoning workflows
-   Simple API-key setup

](/docs/integrations/deepseek.html)[

### xAI Grok

Access xAI's Grok models with real-time knowledge and advanced reasoning. Built for developers who want cutting-edge AI assistance.

-   Grok-2 and Grok-2 mini
-   Real-time knowledge from X data
-   128K context window
-   Vision capabilities

](/docs/integrations/xai.html)[

### Z.ai

Use GLM-family models through Z.ai's OpenAI-compatible API for high-throughput coding and agentic workflows.

-   GLM coding and reasoning models
-   OpenAI-compatible API surface
-   High-performance inference
-   API-key authentication

](/docs/integrations/zai.html)[

### Sakana AI

Use Fugu's multi-agent orchestration models through Sakana AI's OpenAI-compatible API for complex reasoning and long-horizon coding tasks.

-   Fugu and Fugu Ultra orchestration models
-   OpenAI-compatible API surface
-   1M token context window
-   API-key authentication

](/docs/integrations/sakana.html)[

### Cerebras

Fastest

Lightning-fast inference at over 2000 tokens per second. Powered by the world's largest AI chip for near-instant responses.

-   Llama 3.1 8B and 70B models
-   2000+ tokens per second
-   128K context window
-   Competitive pricing

](/docs/integrations/cerebras.html)[

### NVIDIA

Connect to NVIDIA-hosted models through NVIDIA's OpenAI-compatible inference endpoint, including DeepSeek, Mistral, and NVIDIA model families.

-   NVIDIA-hosted model catalog
-   OpenAI-compatible chat completions
-   GPU-backed inference infrastructure
-   Good fit for enterprise GPU stacks

](/docs/integrations/nvidia.html)[

### LLMGateway

Enterprise

Enterprise AI gateway with unified API access to multiple providers. Smart routing, caching, and observability for production applications.

-   Multi-provider access
-   Automatic failover
-   Response caching
-   Cost optimization

](/docs/integrations/llmgateway.html)[

### Azure AI Foundry

Enterprise

Enterprise-grade AI models with Azure security and compliance. Access OpenAI, Llama, and Mistral through Azure infrastructure.

-   GPT-4o, Llama, Mistral models
-   API Key, Entra ID, and Managed Identity auth
-   Regional data residency
-   SOC 2, HIPAA, GDPR compliance

](/docs/integrations/azure-foundry.html)[

### GCP Vertex AI

Enterprise

Google's Gemini models and open-source alternatives through Vertex AI. Enterprise infrastructure with Google Cloud security.

-   Gemini 1.5 Pro, 2.0 Flash
-   2 million token context
-   Model Garden open-source models
-   Google Cloud IAM

](/docs/integrations/gcp-vertex.html)

**Default choice:** OpenRouter is the default provider for Autohand CLI. It gives you immediate access to the best models with a single API key.

## Local providers

Local providers run AI models directly on your machine. Your code never leaves your computer, and you can work without an internet connection.

[

### Ollama

Easy setup

The simplest way to run local models. One-command installation with automatic GPU detection on macOS, Linux, and Windows.

-   Simple installation and model management
-   Cross-platform support
-   Automatic GPU acceleration
-   Large model library

](/docs/integrations/ollama.html)[

### MLX

Apple Silicon

Apple's machine learning framework optimized for M1, M2, M3, and M4 chips. Native Metal acceleration for exceptional performance.

-   Native Apple Silicon optimization
-   Unified memory efficiency
-   Metal GPU acceleration
-   macOS only

](/docs/integrations/mlx.html)[

### llama.cpp

Advanced

High-performance C++ inference engine. Maximum flexibility and control for power users who want to fine-tune every parameter.

-   Maximum performance potential
-   GGUF model format
-   Extensive configuration options
-   Cross-platform support

](/docs/integrations/llama-cpp.html)

## Choosing a provider

Select a provider based on your priorities:

| Priority | Recommended Provider |
|---|---|
| Best model quality | OpenRouter or OpenAI |
| Fastest inference | Cerebras (2000+ tokens/sec) |
| AWS enterprise deployment | AWS Bedrock |
| Enterprise compliance | AWS Bedrock, Azure AI Foundry, or GCP Vertex AI |
| Long context (2M tokens) | GCP Vertex AI (Gemini) |
| Multi-provider management | LLMGateway |
| Cost-sensitive coding models | DeepSeek or Z.ai |
| Multi-agent orchestration | Sakana AI |
| NVIDIA-hosted inference | NVIDIA |
| Real-time knowledge | xAI Grok |
| Complete privacy | Ollama or MLX |
| Offline work | Ollama, MLX, or llama.cpp |
| No API costs | Any local provider |
| Apple Silicon performance | MLX |

## Switching providers

Switch between providers at any time using the CLI or configuration file.

### Using CLI flags

``` bash
# Use OpenRouter (default)
autohand --provider openrouter --model nvidia/nemotron-3-super-120b-a12b:free

# Use AWS Bedrock
AWS_PROFILE=enterprise-prod autohand --provider bedrock --model us.anthropic.claude-3-5-sonnet-20241022-v2:0

# Use DeepSeek
autohand --provider deepseek --model deepseek-v4-flash

# Use Ollama
autohand --provider ollama --model codellama:13b

# Use MLX
autohand --provider mlx --model codellama-7b-instruct

# Use llama.cpp
autohand --provider llamacpp --model codellama-7b
```

### Using configuration

Set your default provider in `~/.autohand/config.json`:

``` json
{
  "provider": "openrouter",
  "model": "nvidia/nemotron-3-super-120b-a12b:free"
}
```

### During a session

Switch models without restarting:

``` bash
# Switch to a different model
/model ollama/codellama:13b

# Switch to a different provider
/model openrouter/nvidia/nemotron-3-super-120b-a12b:free

# Configure enterprise provider details interactively
/model bedrock
```

## Provider comparison

### Cloud providers

| Provider | Best for | Authentication | API style |
|---|---|---|---|
| OpenRouter | Broad model access | API key | OpenAI-compatible |
| OpenAI | Direct OpenAI models | API key or ChatGPT auth | OpenAI native |
| AWS Bedrock | AWS enterprise workloads | AWS credentials/profile/IAM or Bedrock API key | Converse and OpenAI-compatible |
| DeepSeek | Coding and reasoning value | API key | OpenAI-compatible |
| xAI Grok | Grok models | API key | OpenAI-compatible |
| Z.ai | GLM-family inference | API key | OpenAI-compatible |
| Sakana AI | Multi-agent orchestration | API key | OpenAI-compatible |
| Cerebras | Low-latency inference | API key | OpenAI-compatible |
| NVIDIA | GPU-hosted model catalog | API key | OpenAI-compatible |
| Azure AI Foundry | Azure enterprise deployments | API key, Entra ID, or Managed Identity | Azure OpenAI |
| GCP Vertex AI | Google Cloud and Gemini | Google Cloud access token | Vertex AI OpenAPI endpoint |

### Local providers

| Feature | Ollama | MLX | llama.cpp |
|---|---|---|---|
| Setup difficulty | Easy | Medium | Advanced |
| Model quality | Good | Good | Good |
| Offline capable | Yes | Yes | Yes |
| Cost | Free | Free | Free |
| macOS | Yes | Apple Silicon | Yes |
| Linux | Yes | No | Yes |
| Windows | Yes | No | Yes |

Common questions

## model-provider layer integration FAQ

### How do I configure the Autohand model-provider layer integration?

Choose a provider and model with the Autohand CLI, `/model`, or your Autohand configuration file, then set the credential or endpoint named in the provider guide.

### What does the Autohand model-provider layer integration require?

Cloud provider credentials for hosted APIs, or a supported local runtime and model files.

### What limitations should I know about?

Model IDs, context limits, pricing, quotas, and regional access are provider-controlled and can change independently of Autohand.