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Description

Claude Opus 5.5 is a frontier AI model from Anthropic built for coding, research, business analysis, computer use, and complex agentic workflows. The model is particularly suited to long-running software engineering tasks such as codebase migrations, audits, debugging, optimization, and large-scale refactoring. Anthropic also positions Opus 5.5 for professional knowledge work including financial analysis, legal workflows, research reports, spreadsheets, presentations, and business automation. Compared with Claude Opus 5, the model is designed to use fewer tokens, generate responses more quickly, and reduce typical workload costs. Its communication style has also been refined to make outputs clearer, easier to scan, and more consistent with user-defined writing requirements. Opus 5.5 includes stronger defenses against prompt injection and is less likely to take irreversible or out-of-bounds actions during autonomous tasks. Enterprise safety features include action classification, an auditable open-source sandbox, code review capabilities, preserved thinking protections, and configurable safeguards for sensitive domains. The model supports zero data retention and is available with additional verification programs for vetted life sciences and cybersecurity organizations. Claude Opus 5.5 is accessible through Anthropic’s applications and API as well as AWS, Google Cloud, and Microsoft Azure.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Cherry Studio
Hermes Agent
Model Context Protocol (MCP)
OfoxAI
OpenClaw
Python
Qwen Code
Anything
Bind AI
Claude Security
Dessix
GitHub Copilot
GitHub Copilot CLI
Higgsfield Supercomputer
OpenTag
Qwen
Qwen Studio
RubyMine
Solidity
Xcode

Integrations

Cherry Studio
Hermes Agent
Model Context Protocol (MCP)
OfoxAI
OpenClaw
Python
Qwen Code
Anything
Bind AI
Claude Security
Dessix
GitHub Copilot
GitHub Copilot CLI
Higgsfield Supercomputer
OpenTag
Qwen
Qwen Studio
RubyMine
Solidity
Xcode

Pricing Details

$4 per 1M tokens (input)
$4 per million input tokens and $20 per million output tokens.

Cache reads, which account for most costs in agentic and coding workloads, are priced at just $0.20 per million tokens which is 60% cheaper than Opus 5. Opus 5.5 also delivers output over 30% faster than its predecessor.
Free Trial
Free Version

Pricing Details

$2 per 1M (input)
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Anthropic

Founded

2021

Country

United States

Website

claude.ai

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

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