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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
Ornith-1.0 represents an innovative family of models tailored specifically for coding tasks that require agentic capabilities. This family encompasses a wide range of models, from the compact 9B Dense versions ideal for deployment on edge devices to the expansive 397B MoE frontier-scale models designed for peak performance, including variants such as 9B Dense, 31B Dense, 35B MoE, and 397B MoE. Built upon the foundational strengths of pretrained models like Gemma 4 and Qwen 3.5, Ornith-1.0 excels in achieving top-tier performance among open-source models that are similar in size when evaluated against coding benchmarks. A significant breakthrough of this model is its self-improving training framework, which effectively learns to produce both solution rollouts and the tailored scaffolds that direct those rollouts. Rather than depending on static, human-crafted harnesses, Ornith-1.0 perceives the scaffold as a dynamic entity that evolves alongside the policy, enabling the model to optimize both the orchestration of tasks and the resulting solutions in tandem. This dual optimization approach enhances the model's adaptability and effectiveness in real-world coding scenarios.
API Access
Has API
API Access
Has API
Integrations
Amazon Bedrock
Azure OpenAI Service
C++
Charlie
ChatGPT Pro
Claw Code
Flowise
GPT-5.1-Codex
Higgsfield Supercomputer
IntelliJ IDEA
Integrations
Amazon Bedrock
Azure OpenAI Service
C++
Charlie
ChatGPT Pro
Claw Code
Flowise
GPT-5.1-Codex
Higgsfield Supercomputer
IntelliJ IDEA
Pricing Details
$2.50 per 1M tokens (input)
Free Trial
Free Version
Pricing Details
Free
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
OpenAI
Founded
2015
Country
United States
Website
openai.com
Vendor Details
Company Name
DeepReinforce
Country
United States
Website
deep-reinforce.com/ornith_1_0.html
