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Average Ratings 0 Ratings

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Description

GPT-5.6 Terra is OpenAI’s balanced GPT-5.6 model for users who need strong performance across everyday work, development tasks, enterprise workflows, and technical analysis. The model is part of the GPT-5.6 family alongside Sol and Luna, with Terra positioned as the middle tier for capable, cost-efficient use. Terra is described as having competitive performance to GPT-5.5 while being 2x cheaper, making it useful for teams that want advanced capability without always using the flagship model. It supports coding workflows, agentic tasks, cybersecurity-related defensive work, biology workflows, knowledge work, and tool-assisted automation. In benchmark previews, Terra appears alongside Sol and Luna in evaluations for coding, biology, ExploitBench, and ExploitGym. The model benefits from the GPT-5.6 safeguard stack, which includes model-level refusals for prohibited cyber assistance, real-time cyber and biology misuse classifiers, and account-level risk review. These safeguards are designed to preserve access to legitimate work such as code review, debugging, vulnerability research, patch development, security education, and defensive testing. GPT-5.6 Terra is planned for availability through the API, Codex, and broader OpenAI products after the limited preview period. GPT-5.6 Terra helps teams get a balanced model for high-quality AI work when they need strong reasoning and automation at a lower cost than Sol.

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 Atlas Yes 
ChatGPT Plus Yes 
ChatGPT Pro Yes 
Databricks Yes 
Dessix Yes 
Flowise Yes 
JavaScript Yes 
LaunchLemonade Yes 
Microsoft 365 Yes 
Microsoft 365 Copilot Yes 
Novita AI No 
Odysseus No 
OpenAI Yes 
PHP Yes 
Ruby Yes 

Integrations

Hermes Agent Yes 
OpenClaw Yes 
Python Yes 
AiAssistWorks No 
C No 
ChatGPT Atlas No 
ChatGPT Plus No 
ChatGPT Pro No 
Databricks No 
Dessix No 
Flowise No 
JavaScript No 
LaunchLemonade No 
Microsoft 365 No 
Microsoft 365 Copilot No 
Novita AI Yes 
Odysseus Yes 
OpenAI No 
PHP No 
Ruby No 

Pricing Details

$2 per 1M tokens (input)
$2 input / $12 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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