Models & Providers

ARES routes LLM requests across multiple providers through a single API. You do not call providers directly — ARES selects the appropriate model based on the agent configuration and handles credentials, rate limits, and failover transparently.

Available models

How model selection works

You do not specify a model directly in your API calls. Instead, you specify an agent_type, and each agent is configured with a model tier.

# This request is routed to whichever model the "product" agent is configured to use
curl -X POST https://api.ares.dirmacs.com/v1/chat \
  -H "Authorization: Bearer ares_xxx" \
  -H "Content-Type: application/json" \
  -d '{"message": "Compare these two options", "agent_type": "product"}'

The mapping between agents and models is configured by your tenant administrator. A typical setup might look like:

This design means you can upgrade an agent’s underlying model without changing any client code.

Provider architecture

ARES uses a named-provider system. Each provider is configured with its API endpoint, credentials, and rate limits. Models reference their provider by name.

┌─────────────┐
│  Your App   │
│  agent_type │
└──────┬──────┘
       │
       ▼
┌─────────────┐     ┌──────────┐
│    ARES     │────▶│   Groq   │  fast, balanced
│   Router    │     └──────────┘
│             │     ┌──────────┐
│             │────▶│Anthropic │  powerful
│             │     └──────────┘
│             │     ┌──────────┐
│             │────▶│  NVIDIA  │  deepseek
│             │     └──────────┘
│             │     ┌──────────┐
│             │────▶│  Ollama  │  local
└─────────────┘     └──────────┘

Provider details

Groq — High-throughput inference on custom LPUs. Extremely fast response times. Hosts open-source models (Llama, Mixtral). Free tier available with rate limits.

Anthropic — Claude models. Best-in-class for complex reasoning, instruction following, and safety. Requires a paid API key.

NVIDIA (DeepSeek) — NVIDIA-hosted DeepSeek models via the NVIDIA AI API. Strong at code generation and structured technical output.

Ollama — Self-hosted, local inference. No external API calls. Useful for development, air-gapped environments, or when you need to keep data on-premises.

Rate limits

Rate limits are enforced per provider and per tenant. The following are default limits for the Groq free tier:

Anthropic and NVIDIA rate limits depend on your API plan with those providers. ARES surfaces rate limit errors transparently:

{
  "error": "Rate limit exceeded for provider 'groq'",
  "code": "RATE_LIMIT_EXCEEDED",
  "retry_after": 60
}

Tenant-level rate limits and quotas are configured separately by your administrator and enforced by ARES regardless of provider limits.

Adding your own providers

If you are self-hosting ARES, you can add providers in your ares.toml configuration:

[[providers]]
name = "my-openai"
kind = "openai"
api_base = "https://api.openai.com/v1"
api_key_env = "OPENAI_API_KEY"

[[models]]
name = "gpt-4o"
provider = "my-openai"
model_id = "gpt-4o"
tier = "powerful"

Any provider that exposes an OpenAI-compatible API (vLLM, Together AI, Fireworks, etc.) can be added using the openai provider kind.

Choosing the right tier

When in doubt, start with balanced. It provides the best trade-off between quality, speed, and cost for most use cases.