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Description
Gemma 4 is an advanced AI model developed by Google as part of its Gemini architecture, designed to deliver strong performance while remaining accessible to developers. The model is optimized to run on a single GPU or TPU, allowing more organizations and researchers to experiment with powerful AI technology. Gemma 4 improves natural language understanding and generation, making it suitable for applications such as chatbots, text analysis, and automated content creation. Its architecture enables the model to process complex language patterns while maintaining efficient computational performance. Developers can integrate Gemma 4 into various AI projects that require intelligent text processing or conversational capabilities. The model is designed with scalability in mind, allowing it to support both research experiments and production systems. By offering high-performance AI in a more accessible format, Gemma 4 lowers the barrier for developing sophisticated AI solutions. Its flexibility makes it useful for industries ranging from technology and education to business automation. Researchers can also use the model to explore new AI techniques and improve language processing systems. Overall, Gemma 4 represents a step forward in making powerful AI models easier to deploy and use.
Description
K2 Horizon comprises a network of six open models, including the 375B-A23B, 36B-A4B, 32B, 7B, 3.7B, and 0.9B, all engineered to excel in various domains such as reasoning, mathematics, coding, agentic tasks, and overall capabilities. These models share a unified architecture, vocabulary, training techniques, interfaces, evaluation frameworks, and deployment tools, facilitating seamless transitions between sizes and dynamic workload management. The fleet's flagship, the 375B-A23B model, is particularly adept at handling intricate reasoning, software development, research projects, and long-term agentic functions, while the 32B and 36B-A4B models focus on delivering robust local deployment solutions. Notably, the 36B-A4B model features an innovative Mixture-of-Value Attention mechanism, which merges sparse attention with Mixture-of-Experts layers, allowing it to engage approximately 4 billion parameters per token and compete closely with the performance of the denser 32B model. This architecture not only enhances flexibility but also maximizes resource efficiency across a wide range of applications.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
AiAssistWorks
C++
Cloudflare AI Gateway
F#
Gemini Enterprise
Hugging Face
Julia
Keras
LFM2.5
MedGemma
Integrations
AiAssistWorks
C++
Cloudflare AI Gateway
F#
Gemini Enterprise
Hugging Face
Julia
Keras
LFM2.5
MedGemma
Pricing Details
Free
Open source
Free Trial
Free Version
Pricing Details
No price information available.
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
Founded
1998
Country
United States
Website
deepmind.google/models/gemma/
Vendor Details
Company Name
Institute of Foundation Models
Founded
2025
Country
United States
Website
ifm.ai/blog/k2/