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Sakana AI: Sakana Namazu

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Model Card

Sakana Namazu is a Japanese-specialized large language model from Tokyo-based Sakana AI, built on Moonshot AI's Kimi K2.6 and further tuned on Sakana's own data.

The tuning targets the nuances of Japanese language and business practice, including keigo honorifics, business customs, and everyday slang that general-purpose models often miss. Sakana AI reports the tuning also improves neutrality and factual accuracy on topics specific to Japan, while keeping reasoning, knowledge, and coding performance in line with the base model.

The API is OpenAI-compatible and ships with built-in web search and code execution tools, so it can be dropped into existing agent and chat integrations with minimal changes.

Sakana Namazu suits developers building Japanese-language products, such as customer support, business writing, and research or coding agents that need to work naturally in Japanese.

Context Window 262K

tokens

Max Output 66K

tokens

Input Cost $0.95

per million tokens

Output Cost $4

per million tokens

Release Date Aug 11, 2026

 

Code Example

Add AI to your app with the Puter.js AI API, no API keys or setup required.

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms").then(response => {
    document.body.innerHTML = response.message.content;
});
<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

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Fugu Ultra v2

Fugu Ultra v2 is Sakana AI's second-generation orchestration model, succeeding the original Fugu Ultra. Rather than a single model, it routes each request across a pool of specialist agents, assigning Thinker, Worker, and Verifier roles behind one OpenAI-compatible endpoint. The approach builds on Sakana's TRINITY and Conductor research from ICLR 2026. Sakana reports v2 reaches its scores without Fable 5, Fable 5.1, or GPT-6-Astra in its agent pool. On Chartography, a visual and structured-data reasoning benchmark, it scores 48.3 versus Opus 5's 27.3 and Fable 5's 29.5. On the DeepSWE software engineering benchmark it scores 74.3. Sakana ranks it best or joint-best on 5 of 8 published benchmarks. Pricing matches the original Fugu Ultra, $5 per million input tokens, $30 per million output tokens, with a 1M token context window. It suits complex multi-step reasoning, coding agents, and document or chart analysis, for teams avoiding dependence on one flagship provider.

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Fugu Ultra

Fugu Ultra is a learned multi-agent orchestration system from Tokyo-based Sakana AI that routes tasks across a swappable pool of frontier LLMs behind a single OpenAI-compatible endpoint. Rather than relying on one monolithic model, Fugu Ultra dynamically assigns Thinker, Worker, and Verifier roles to specialist agents, then synthesizes their outputs into a single response. The underlying coordination is grounded in Sakana's TRINITY and Conductor research, published at ICLR 2026. It targets demanding, multi-step problems: complex reasoning, code review, agentic workflows, cybersecurity analysis, and research tasks. On LiveCodeBench it scores 93.2, ahead of several frontier competitors, and it matches leading models on GPQA-Diamond and Humanity's Last Exam. Fugu Ultra is a strong choice for developers who need frontier-level quality on hard tasks without committing to a single model provider.

Frequently Asked Questions

How do I use Sakana Namazu?

Sakana Namazu is no longer available through Puter.js. Explore other AI models for alternatives.

What is the pricing for Sakana Namazu?
Sakana Namazu costs $0.95 per 1M input tokens and $4 per 1M output tokens.
Price per 1M tokens
Input$0.95
Output$4
Who created Sakana Namazu?

Sakana Namazu was created by Sakana AI and released on Aug 11, 2026.

What is the context window of Sakana Namazu?

Sakana Namazu supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.

What is the max output length of Sakana Namazu?

Sakana Namazu can generate up to 66K tokens in a single response.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Sakana Namazu API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

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