Models & Providers

Supported providers

Provider	Config key	Endpoint
Groq	groq	https://api.groq.com/openai/v1/chat/completions
Cerebras	cerebras	https://api.cerebras.ai/v1/chat/completions
Gemini	gemini	https://generativelanguage.googleapis.com/v1beta/models/{model}:generateContent
OpenRouter	openrouter	https://openrouter.ai/api/v1/chat/completions
DeepSeek	deepseek	https://api.deepseek.com/chat/completions

OpenRouter is itself a router: it forwards each request to a provider that hosts the model, which makes it the provider that serves the most aliases below.

Model aliases

An alias lists provider models in a fixed order. Nuabase uses the first one whose provider you supplied an API key for.

Alias	Tries, in order
fast (default)	Cerebras qwen-3.8-27b → Groq openai/gpt-oss-120b → OpenRouter z-ai/glm-5.3-flash
gemini	Gemini gemini-3.8-flash → OpenRouter google/gemini-3.8-flash
deepseek	DeepSeek deepseek-v4-pro → OpenRouter deepseek/deepseek-v4-pro-0813
qwen	OpenRouter qwen/qwen3.8-2.4t-a95b
sonnet	OpenRouter anthropic/claude-sonnet-5.5
opus	OpenRouter anthropic/claude-opus-5.5
haiku	OpenRouter anthropic/claude-haiku-4.5
kimi	OpenRouter moonshotai/kimi-k3
gpt	OpenRouter openai/gpt-6.1-sol

// Client default
const nua = Nua.direct({
  providers: { openrouter: { apiKey: process.env.OPENROUTER_API_KEY! } },
  model: { alias: 'sonnet' },
});

// Per call
await nua.get('Summarize this', {
  input: text,
  output: { name: 'summary', schema: z.string() },
  model: { alias: 'kimi' },
});

On a local agent, only Claude Code accepts aliases, and only haiku, sonnet, and opus, which it maps to its own models.

Explicit provider models

To use a model no alias covers, name the provider and the provider’s own model ID:

await nua.get('Summarize this', {
  input: text,
  output: { name: 'summary', schema: z.string() },
  model: { provider: 'groq', model: 'openai/gpt-oss-120b' },
});

The provider must be one you configured a key for. For Gemini, use bare model IDs such as gemini-3.8-flash, not models/gemini-3.8-flash.

Picking a model

• Latency-sensitive work such as parsing user input in a form: fast. Cerebras and Groq serve open models at very high token rates.
• Harder extraction or reasoning: sonnet, opus, gpt, or gemini.
• Bulk enrichment of many rows: start with fast and move up only for fields where it isn’t accurate enough. nua.list() already amortizes the prompt over many rows.

Pricing and rate limits are set by each provider. Check their dashboards for current numbers.