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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.
Description
Qwen3.8-Flash-Next represents an open-weight multimodal Mixture-of-Experts architecture and serves as an initial glimpse into the design intended for Qwen4. This model strategically enhances attention mechanisms, residual pathways, embeddings, and optimization techniques to boost its capabilities, improve computational efficiency, expand model capacity, and ensure training stability. Its innovative hybrid architecture merges Gated DeltaNet, which adeptly compresses past information, with Qwen Sparse Attention, enabling the selection of significant context at a micro-block level to lessen both attention and indexing costs associated with lengthy sequences. The Gated Residual feature broadens the residual pathway into four streams, dynamically managing the flow of information across different layers. Additionally, the N-gram Embedding integrates large-scale local-pattern memory with minimal added computation per token, and it can be transferred to host memory for further efficiency. The model is structured around a 125B-parameter main network supplemented by 51B parameters dedicated to N-gram embeddings, activating only 6B parameters for each token processed. This sophisticated framework highlights the ongoing advancements in machine learning architectures, setting a promising stage for future developments.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Alibaba Cloud
No
Alibaba Cloud Model Studio
No
Cherry Studio
No
Cline
No
ClinePass
No
Happy Shrimp 1.0
No
Hermes Agent
No
Model Context Protocol (MCP)
No
ModelScope
No
Novita AI
No
Integrations
Alibaba Cloud
Yes
Alibaba Cloud Model Studio
Yes
Cherry Studio
Yes
Cline
Yes
ClinePass
Yes
Happy Shrimp 1.0
Yes
Hermes Agent
Yes
Model Context Protocol (MCP)
Yes
ModelScope
Yes
Novita AI
Yes
Pricing Details
$6 per 1M tokens (input)
$6 per 1M tokens (input), $36 per 1M tokens (output)
Free Trial
No
Free Version
No
Pricing Details
$2 per 1M (input)
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Sakana AI
Founded
2023
Country
Japan
Website
sakana.ai/fugu-1-1-claude-code-interface/
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
qwen.ai/blog