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What is Sakana Fugu Ultra?

Sakana Fugu Ultra is the advanced, performance-focused model in the Sakana Fugu platform, designed to coordinate multiple expert AI agents for difficult and high-stakes work. It is built for users who need stronger results on complex multi-step tasks than a single model or basic AI assistant can usually provide. Through one OpenAI-compatible API, Fugu Ultra dynamically selects and coordinates agents from a powerful model pool while presenting the experience as one model. This allows teams to use multi-agent intelligence without manually building agent workflows, assigning roles, or switching between different providers. Fugu Ultra is optimized for demanding use cases such as software engineering, code review, Kaggle competitions, paper reproduction, cybersecurity analysis, scientific problem solving, literature investigations, patent analysis, and autonomous research. The system is grounded in research-driven orchestration methods, including TRINITY and the Conductor, which focus on learning how to route tasks, coordinate agents, and create effective collaboration patterns. Compared with the standard Fugu model, Fugu Ultra uses a deeper expert pool to prioritize quality on harder problems. It is designed for workloads where precision, reasoning depth, completeness, and reliability are more important than low latency alone. Organizations can opt out of specific models or providers in the agent pool to meet data, privacy, compliance, procurement, or internal governance requirements. Fugu Ultra also includes fixed pay-as-you-go pricing for input, output, and cached input tokens, with higher rates for very long context usage. Sakana Fugu Ultra helps technical teams plug advanced multi-agent orchestration into existing workflows while reducing single-vendor dependency and improving performance on challenging AI tasks.

What is Abliterated Large V2?

Abliterated Large V2 is an advanced text-based reasoning model developed by Abliteration AI for cybersecurity analysis, autonomous AI agents, software development, and adversarial model evaluation. The model is based on Z.ai's GLM 5.3 architecture and has undergone weight-level modifications intended to reduce refusal behavior. This modification process, known as abliteration, changes internal model representations associated with rejecting certain requests rather than relying on prompt-based jailbreak techniques. Its one-million-token context window enables the processing of large software repositories, extensive technical documentation, security research materials, and long-running agent workflows. The model supports advanced code generation, debugging, technical reasoning, and multistep programming tasks requiring interaction with external tools. Cybersecurity applications include vulnerability analysis, authorized penetration testing, exploit research, security validation, and automated assessment of software weaknesses. AI safety researchers can use the model to evaluate agent behavior, test security boundaries, and examine how systems respond to adversarial scenarios. Native tool calling enables the model to interact with supported external applications, development environments, and automated testing infrastructure. Structured output functionality allows developers to generate machine-readable responses for integration with security tools and programmatic workflows. Abliterated Large V2 is hosted in FP8 precision and provides access through OpenAI-compatible chat completion and response endpoints, as well as an Anthropic-style messages interface. The model is available through Abliteration AI and third-party inference providers, with automatic prompt caching, configurable reasoning capabilities, and default zero-retention handling of API inputs and outputs.

Media

Media

Integrations Supported

Claude Code
Fugu-Ultra v1.1
OpenRouter
Sakana Fugu
Vercel AI Gateway

Integrations Supported

Abliteration.ai
Venice.ai

API Availability

Has API

API Availability

Has API

Pricing Information

$20 per month

Pricing Information

$3 per 1M tokens (input)
$3.00 per 1 million input tokens, $5.00 per 1 million output tokens, and $0.30 per 1 million cached input tokens

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

Abliteration.ai

Date Founded

2025

Company Location

United States

Company Website

abliteration.ai/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

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