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Description
Edgee operates as an AI intermediary that integrates seamlessly with your application and various large language model providers, functioning as an intelligence layer at the edge that minimizes prompt size before they are sent to the model, ultimately decreasing token consumption, lowering expenses, and enhancing response times without requiring alterations to your current codebase. Users can access Edgee via a single API that is compatible with OpenAI, allowing it to implement various edge policies, including smart token compression, routing, privacy measures, retries, caching, and financial oversight, before passing the requests to chosen providers like OpenAI, Anthropic, Gemini, xAI, and Mistral. The advanced token compression feature efficiently eliminates unnecessary input tokens while maintaining the meaning and context, which can lead to a substantial reduction of up to 50% in input tokens, making it particularly beneficial for extensive contexts, retrieval-augmented generation (RAG) workflows, and multi-turn conversations. Furthermore, Edgee allows users to label their requests with bespoke metadata, facilitating the monitoring of usage and expenses by different criteria such as features, teams, projects, or environments, and it sends notifications when there is an unexpected increase in spending. This comprehensive solution not only streamlines interactions with AI models but also empowers users to manage costs and optimize their application’s performance effectively.
Description
MiMo-V2-Flash is a large language model created by Xiaomi that utilizes a Mixture-of-Experts (MoE) framework, combining remarkable performance with efficient inference capabilities. With a total of 309 billion parameters, it activates just 15 billion parameters during each inference, allowing it to effectively balance reasoning quality and computational efficiency. This model is well-suited for handling lengthy contexts, making it ideal for tasks such as long-document comprehension, code generation, and multi-step workflows. Its hybrid attention mechanism integrates both sliding-window and global attention layers, which helps to minimize memory consumption while preserving the ability to understand long-range dependencies. Additionally, the Multi-Token Prediction (MTP) design enhances inference speed by enabling the simultaneous processing of batches of tokens. MiMo-V2-Flash boasts impressive generation rates of up to approximately 150 tokens per second and is specifically optimized for applications that demand continuous reasoning and multi-turn interactions. The innovative architecture of this model reflects a significant advancement in the field of language processing.
API Access
Has API
API Access
Has API
Integrations
Claude
Claude Code
Gemini
Grok
Hugging Face
Mistral AI
OpenAI
Xiaomi MiMo
Xiaomi MiMo Studio
Integrations
Claude
Claude Code
Gemini
Grok
Hugging Face
Mistral AI
OpenAI
Xiaomi MiMo
Xiaomi MiMo Studio
Pricing Details
Free
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
Edgee
Founded
2024
Country
United States
Website
www.edgee.ai/
Vendor Details
Company Name
Xiaomi Technology
Founded
2010
Country
China
Website
mimo.xiaomi.com/blog/mimo-v2-flash