Fugu-Ultra v1.1 Description

Fugu-Ultra v1.1 represents the enhanced multi-agent orchestration model developed by Sakana AI, designed for intricate coding tasks, agentic functions, and sophisticated reasoning capabilities. Instead of depending on a singular model, it adeptly manages a variety of cutting-edge models, strategically selecting and merging specialized agents tailored for individual tasks, all while offering a unified model interface. The latest orchestration upgrade in v1.1 features the inclusion of newer frontier models, resulting in improved performance metrics across all monitored benchmarks, achieving enhancements of up to 7.9 points compared to v1.0, with particularly notable successes on ProgramBench and Terminal Bench 2.1. In addition, Fugu can now seamlessly integrate within Claude Code through endpoints that are compatible, allowing a collaborative ensemble of models to function within the user-friendly terminal environments for coding, debugging, reviewing, and executing scripts. Users can easily set up this integration using a one-command installer on Ubuntu and macOS, while alternative manual configurations are provided for Windows and other systems, ensuring accessibility across diverse platforms. This advancement not only streamlines workflows but also enhances productivity by leveraging the strengths of multiple specialized agents.

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Pricing

Pricing Starts At:
$6 per 1M tokens (input)
Pricing Information:
$6 per 1M tokens (input), $36 per 1M tokens (output)

Integrations

API:
Yes, Fugu-Ultra v1.1 has an API
View Integrations

Reviews - 1 Verified Review

Total
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Company Details

Company:
Sakana AI
Year Founded:
2023
Headquarters:
Japan
Website:
sakana.ai/fugu-1-1-claude-code-interface/

Media

Fugu-Ultra v1.1 Screenshot 1
Fugu-Ultra v1.1 Screenshot 1 Fugu-Ultra v1.1 Screenshot 2
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Product Details

Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Online Support

Fugu-Ultra v1.1 Features and Options

Fugu-Ultra v1.1 User Reviews

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  • Name: Anonymous (Verified)
    Job Title: Developer
    Length of product use: Less than 6 months
    Used How Often?: Daily
    Role: User
    Organization Size: 26 - 99
    Features
    Ease
    Pricing
    Likelihood to Recommend to Others
    1 2 3 4 5 6 7 8 9 10

    Really interesting model

    Date: Jul 27 2026

    Summary: Five stars from me. Fugu-Ultra v1.1 feels like one of the more creative approaches to developer AI right now because it treats coding and reasoning as orchestration problems, not just model-size problems.

    For developers building agents, coding assistants, research tools, or advanced automation workflows, that is a really compelling direction. It feels especially promising for hard multi-step tasks where one model may not be enough, but a coordinated team of specialist agents can get further.

    Positive: Fugu-Ultra v1.1 is really interesting from a developer’s point of view because it feels like a different approach from the usual “one giant model does everything” setup. Instead, it acts more like an intelligent orchestration layer that can route work across multiple frontier models and agent patterns.

    That makes a lot of sense for coding and agentic workflows. Real development tasks are messy, and different parts of the job need different strengths: planning, repo search, debugging, terminal work, reasoning, code generation, and cleanup.

    I also like that Sakana added a Claude Code-compatible interface. Being able to use Fugu directly inside developer workflows makes it feel much more practical than something you only test in a browser or benchmark page.

    The benchmark gains are impressive too. If the reported improvements on coding and terminal tasks hold up in real projects, Fugu-Ultra v1.1 could be a strong option for developers building serious coding agents.

    Negative: The main downside is that orchestration adds complexity. When a system is coordinating multiple models behind the scenes, I want strong transparency, logging, debugging tools, and predictable behavior before I trust it deeply in production.

    I would also want to test latency and cost carefully. Multi-agent systems can be powerful, but they can also become expensive or slow if they overthink simple tasks.

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