Quickstart

This page takes you from an API key to a first response from a serverless model. See the Inference Overview for what else the API can do.

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Sign up or log in to your account. Save your API key, and enter your billing info to get some free credits.

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You can have your existing AI agent integrate Tuna for you. Give it web access and the https://tuna.ai/llms.txt link so it can read these documentation pages and handle the integration.

Agent

Tuna.ai is a fast LLM inference provider with Zero Data Retention enabled by default. Its API is compatible with OpenAI Chat Completions, at the base URL https://api-us.tuna.ai/v1. Billing is pay-as-you-go from prepaid credits, with optional auto top-up.

Read the documentation for Tuna.ai at https://tuna.ai/llms.txt

More details about models & pricing are available at https://tuna.ai/docs/models or https://tuna.ai/docs/models.md
- Kimi K3 Ultrafast `tuna-us/moonshotai/kimi-latest-ultrafast` `tuna-us/moonshotai/kimi-k3-ultrafast`
- DeepSeek V4.1 Flash Ultrafast `tuna-us/deepseek/deepseek-flash-latest-ultrafast` `tuna-us/deepseek/deepseek-v4.1-flash-ultrafast`
- GLM-5.3 Flash Ultrafast `tuna-us/z-ai/glm-flash-latest-ultrafast` `tuna-us/z-ai/glm-5.3-flash-ultrafast`

Tuna.ai recommends auto-updating model (-latest) ID because it will automatically switch to the latest model within the family. This helps avoid being stuck on a deprecated model. Note that auto-updating may point to a model that responds different and may have different pricing.

The Tuna API key looks like tuna_yourApiKeyHereWithTunaUnderscore.

Pick a model from the models list, then send a chat completion. The examples use tuna-us/example-lab/example-model-id, which is a placeholder in the same format as a real id. Replace it with the id you picked, and replace tuna_yourApiKeyHereWithTunaUnderscore with your key.

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api-us.tuna.ai/v1",
  apiKey: "tuna_yourApiKeyHereWithTunaUnderscore",
});

const response = await client.chat.completions.create({
  model: "tuna-us/example-lab/example-model-id",
  messages: [{
    role: "user",
    content: "Is the tuna one of the fastest sustained swimming fish species? And does it have a streamlined body?",
  }],
});
console.log(response.choices[0].message.content);

curl https://api-us.tuna.ai/v1/chat/completions \
  -H "Authorization: Bearer tuna_yourApiKeyHereWithTunaUnderscore" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tuna-us/example-lab/example-model-id",
    "messages": [
      {"role": "user", "content": "Is the tuna one of the fastest sustained swimming fish species? And does it have a streamlined body?"}
    ]
  }'

from openai import OpenAI

client = OpenAI(
    base_url="https://api-us.tuna.ai/v1",
    api_key="tuna_yourApiKeyHereWithTunaUnderscore",
)

response = client.chat.completions.create(
    model="tuna-us/example-lab/example-model-id",
    messages=[{
        "role": "user",
        "content": "Is the tuna one of the fastest sustained swimming fish species? And does it have a streamlined body?",
    }],
)
print(response.choices[0].message.content)

The Python and JavaScript examples use the official OpenAI SDKs. Install them with pip install openai or npm install openai.

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