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Average Ratings 0 Ratings

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Description

GPT-5.6 Sol is OpenAI’s flagship model in the GPT-5.6 series, built for high-end reasoning, coding, scientific analysis, cybersecurity, and agentic automation. The model is designed to handle complex tasks that require planning, iteration, tool coordination, long-horizon reasoning, and careful execution across multiple steps. GPT-5.6 Sol introduces max reasoning effort, giving the model more time to reason deeply through difficult problems. It also introduces ultra mode, which uses subagents to accelerate complex work and extend capability beyond a single-agent workflow. For coding, GPT-5.6 Sol is positioned for command-line workflows, software engineering tasks, debugging, testing, and multi-step tool use. In biology and quantitative research workflows, the model is designed to support genomics analysis and other long-context scientific tasks while using tokens more efficiently than prior models. For cybersecurity, GPT-5.6 Sol supports legitimate defensive work such as vulnerability research, code review, patch development, security education, and defensive testing. The model includes a layered safeguard stack with trained refusals, real-time cyber and biology misuse classifiers, account-level monitoring, differentiated access, human-in-the-loop review, and ongoing red-team testing. GPT-5.6 Sol helps trusted users and organizations access more powerful AI for technical work while maintaining stronger controls around misuse, sensitive requests, and high-risk activity.

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 

Screenshots View All

Screenshots View All

Integrations

Hermes Agent Yes 
OpenClaw Yes 
Python Yes 
AiAssistWorks Yes 
C# Yes 
ChatGPT Yes 
Cherry Studio No 
Cline No 
Codex CLI Yes 
Dart Yes 
GPT-5.1-Codex-Max Yes 
Go Yes 
JetBrains AI Assistant Yes 
Microsoft 365 Copilot Chat Yes 
Microsoft Foundry Yes 
Model Context Protocol (MCP) No 
OfoxAI No 
PHP Yes 
Wazzap AI Yes 
ZeroHuman Yes 

Integrations

Hermes Agent Yes 
OpenClaw Yes 
Python Yes 
AiAssistWorks No 
C# No 
ChatGPT No 
Cherry Studio Yes 
Cline Yes 
Codex CLI No 
Dart No 
GPT-5.1-Codex-Max No 
Go No 
JetBrains AI Assistant No 
Microsoft 365 Copilot Chat No 
Microsoft Foundry No 
Model Context Protocol (MCP) Yes 
OfoxAI Yes 
PHP No 
Wazzap AI No 
ZeroHuman No 

Pricing Details

$4 per 1M tokens (input)
$4 input / $20 output per 1M tokens
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

OpenAI

Founded

2015

Country

United States

Website

openai.com

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

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Alternatives

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