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What is Ornith-1.0?

Ornith-1.0 introduces a groundbreaking suite of models specifically designed for coding tasks that necessitate agent-like capabilities. This collection features a diverse array of models, ranging from the efficient 9B Dense versions suited for edge device deployment to the larger 397B MoE frontier-scale models optimized for maximum performance, including options such as 9B Dense, 31B Dense, 35B MoE, and 397B MoE. Drawing on the robust foundations of pretrained models like Gemma 4 and Qwen 3.5, Ornith-1.0 stands out by delivering top-notch performance among open-source models of comparable sizes when assessed against coding benchmarks. A notable advancement of this model is its innovative self-improving training framework, which adeptly learns to generate both solution rollouts and the customized scaffolds that guide those rollouts. Instead of relying on static, manually crafted structures, Ornith-1.0 treats the scaffold as a fluid entity that evolves in sync with its policy, allowing the model to enhance both task orchestration and solution outcomes simultaneously. This dual-focused optimization significantly boosts the model's versatility and efficacy in practical coding applications, making it a vital tool for developers seeking cutting-edge solutions. As a result, Ornith-1.0 sets a new standard in the realm of coding models, promising advancements that could reshape how coding challenges are approached.

What is MiniMax M3?

MiniMax M3 is an open-weight multimodal foundation model from MiniMax that brings together coding capability, agentic reasoning, native multimodality, and long-context processing in one model. It is designed for demanding AI workflows where a system needs to understand large amounts of information, reason through multi-step tasks, use tools, and work with different input types. MiniMax M3 supports a context window of up to 1 million tokens, making it useful for large code repositories, long documents, multi-file analysis, research workflows, enterprise automation, and persistent agent memory. The model uses MiniMax Sparse Attention, an architecture built to improve efficiency at very long context lengths by reducing the cost of attention. MiniMax M3 is natively multimodal and can work with text, images, and video inputs, allowing it to support richer workflows than text-only language models. It is positioned for coding, software engineering, tool invocation, browser-style retrieval, computer-use-style tasks, and autonomous task decomposition. The model’s architecture includes a large total parameter count with a smaller number of activated parameters, supporting more efficient inference through a mixture-of-experts design. Developers can use MiniMax M3 to build coding assistants, AI agents, document intelligence systems, multimodal analysis tools, and automated enterprise workflows. Its long-context design helps reduce the need to compress or split large inputs, allowing teams to keep more project context available during reasoning. The model is available through open-weight releases and hosted API providers, giving developers multiple ways to test, deploy, or integrate it into applications. MiniMax M3 helps organizations build advanced AI systems that combine long memory, multimodal understanding, coding strength, and agentic execution.

Media

Media

Integrations Supported

APIFree
Alibaba AI Coding Plan
BLACKBOX AI
Claude Code
Clawd.run
Cline
Fireworks AI
Hermes Agent
Kilo Code
MaxHermes
MiniMax Agent
MiniMax Code
MiniMax Mavis
Ollama
OpenClaw
Pi Agent
Roo Code
Tabbit Browser
Together AI
Vision Agents

Integrations Supported

APIFree
Alibaba AI Coding Plan
BLACKBOX AI
Claude Code
Clawd.run
Cline
Fireworks AI
Hermes Agent
Kilo Code
MaxHermes
MiniMax Agent
MiniMax Code
MiniMax Mavis
Ollama
OpenClaw
Pi Agent
Roo Code
Tabbit Browser
Together AI
Vision Agents

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

DeepReinforce

Company Location

United States

Company Website

deep-reinforce.com/ornith_1_0.html

Company Facts

Organization Name

MiniMax

Date Founded

2021

Company Location

Singapore

Company Website

www.minimax.io

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