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What is Sakana Fugu?

Sakana Fugu is a multi-agent AI system that operates like one model while coordinating many underlying expert models behind a single API. The platform is designed to deliver frontier-level performance without forcing users to depend on one model provider or manually manage several separate AI tools. Fugu dynamically chooses which agents should participate in each task and coordinates them through learned collaboration patterns. This approach allows the system to handle complex work such as coding, reasoning, scientific problem solving, code review, security assessment, literature analysis, patent research, and autonomous research workflows. Sakana Fugu is grounded in research on learned orchestration, including TRINITY and the Conductor, which explore how AI systems can route tasks, assign roles, and coordinate communication among multiple agents. Users can access the system through an OpenAI-compatible API and choose between Fugu and Fugu Ultra depending on their workload. Fugu is built for everyday coding, chatbot, review, and productivity use cases where strong performance and lower latency are both important. Fugu Ultra uses a deeper pool of expert agents to improve quality on harder tasks such as Kaggle competitions, paper reproduction, cybersecurity analysis, and technical investigations. Organizations can control which agents, providers, or models are allowed in the pool to meet privacy, data handling, compliance, and procurement needs. The platform offers pay-as-you-go and subscription pricing options, with Fugu Ultra priced separately for input, output, and cached input tokens. Sakana Fugu gives developers, researchers, and enterprises a way to plug multi-agent intelligence into existing workflows while maintaining flexibility, control, and stronger performance on demanding tasks.

What is Claude Haiku 5.5?

Claude Haiku 5.5 is an Anthropic AI model built for high-volume and latency-sensitive AI workloads that require a balance of speed, cost, context capacity, and reasoning. Its primary use cases include classification, routing, information extraction, and subagent tasks within larger AI systems. Claude Haiku 5.5 introduces adaptive thinking, which allows the model to decide when reasoning is needed and how much thinking to apply before producing a response. Adaptive thinking is enabled by default, while the effort parameter gives developers a way to trade response quality against latency and cost. Developers can disable thinking at high effort or below, but Anthropic recommends using effort as the primary mechanism for controlling the model's reasoning behavior. The model provides a 1 million token context window, representing a substantial increase from the 200,000-token context window available with Claude Haiku 4.5. It can generate as many as 128,000 output tokens compared with the previous model's 64,000-token maximum, although thinking tokens are included within the configured output allowance. Browser use is available through the Claude API and Google Cloud, enabling developers to incorporate the model into workflows that require interaction with browser-based environments. Claude Haiku 5.5 uses the newer tokenizer found in Claude 4.7 and later models, resulting in approximately 30% more tokens for the same text compared with Claude Haiku 4.5, depending on the content. The model also changes several API behaviors, including replacing manual extended thinking with adaptive thinking, rejecting non-default sampling parameters and assistant-message prefills, and requiring updated computer-use tooling for supported environments.

Media

Media

Integrations Supported

Claude Code
Vercel AI Gateway

Integrations Supported

Claude Code
Vercel AI Gateway
Aider
Augment Code
BLACKBOX AI
Claude Duet
Claude Whiteboards
Devin
Emergent
GitHub
Java
Julia
Lua
Muses
MyClaw
React
SQL
Scala
Scalestack
XML

API Availability

Has API

API Availability

Has API

Pricing Information

$20/month
API:
$5 per 1M tokens (input)
$30 per 1M tokens (output)
$0.50 per 1M tokens (cached input)

Pricing Information

$0.10 per 1M tokens (input)
For prompts under 100K tokens, it's $0.10 input / $0.50 output per million tokens with cache reads at $0.01. Above 100K tokens, $0.50 input / output $2.50 per million, with cache reads at $0.05.

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Sakana AI

Date Founded

2023

Company Location

Japan

Company Website

sakana.ai/fugu/

Company Facts

Organization Name

Anthropic

Date Founded

2021

Company Location

United States

Company Website

claude.ai

Categories and Features

Agentic AI

Not specified

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Vision Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

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