Models

Fugu

Fugu balances strong performance with low latency, making it the ideal default for everyday work. Fugu, will route to the best model based on the task at hand. You can also opt specific agents out of its pool to meet data, privacy, and compliance constraints.

Fugu Ultra

Fugu Ultra coordinates a deeper pool of expert agents to maximize answer quality on hard, high-stakes problems. Fugu Ultra focuses on maximizing performance, for a higher cost. It routes between one to three agents, depending on the problem.

Benchmark comparison

Reported benchmark scores across Fugu and other frontier models.

Example Usage

These examples use the OpenAI-compatible Responses API. Set your environment variables once, then copy and run the Python or cURL example you need.

# pip install openai
import os
from openai import OpenAI

base_url = os.environ["FUGU_BASE_URL"].rstrip("/")
if not base_url.endswith("/v1"):
    base_url = f"{base_url}/v1"

client = OpenAI(
    api_key=os.environ["FUGU_API_KEY"],
    base_url=base_url,
)

with client.responses.stream(
    model="fugu-ultra",
    input="Explain why streaming is useful in three short bullets.",
) as stream:
    for event in stream:
        if event.type == "response.output_text.delta":
            print(event.delta, end="", flush=True)

    # Full response object assembled from the stream.
    response = stream.get_final_response()

print()
print(response)

Supported endpoints

Fugu currently supports the OpenAI-compatible Chat Completions, Responses, and Models APIs. For generation requests, we strongly recommend using the Responses API, for better performance.

Responses API

Use /v1/responses when you want the Responses API shape, especially for tool use, multimodal input, and proper reasoning or function calls management.

For more details, see the OpenAI Responses API reference.

Supported request fields

Chat Completions

Use /v1/chat/completions when you want the OpenAI Chat Completions API shape.

For more details, see the OpenAI Chat Completions API reference.

Supported request fields

Models API

Use /v1/models to list the models available through the API. This OpenAI-compatible endpoint returns the supported model IDs.

For more details, see the OpenAI Models API reference.

Supported models

Built-in tools

Fugu models support OpenAI-compatible built-in tools in the Responses API. To let the model search the web, add the web_search tool to your request's tools array, just as you would with OpenAI models.

When web search is used, the response can include web search call output. Advance options for the tool are not supported. For more details see the OpenAI web search guide.

# pip install openai
import os
from openai import OpenAI

base_url = os.environ["FUGU_BASE_URL"].rstrip("/")
if not base_url.endswith("/v1"):
    base_url = f"{base_url}/v1"

client = OpenAI(
    api_key=os.environ["FUGU_API_KEY"],
    base_url=base_url,
)

response = client.responses.create(
    model="fugu",
    tools=[{"type": "web_search"}],
    input="Search the web for today's top AI news and summarize it with citations.",
)

print(response.output_text)

Usage fields for Fugu Ultra

Outside of standard Responses API output, Fugu Ultra returns usage fields that separate user-visible model work from orchestration work. Note that different to OpenAI, even though the orchestration tokens are stored in token_details fields. They represent real token usage outside of the input, output tokens, and will be counted in the final price of the request. The price will be the same as standard input and output tokens.

{
  "usage": {
    "input_tokens": 120,
    "output_tokens": 80,
    "total_tokens": 200,
    "input_tokens_details": {
      "cached_tokens": 0,
      "orchestration_input_tokens": 0,
      "orchestration_input_cached_tokens": 0
    },
    "output_tokens_details": {
      "orchestration_output_tokens": 0
    }
  }
}