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What is oMLX?
oMLX is a dedicated MLX server optimized for macOS, which significantly boosts the speed and efficiency of local AI tasks on Apple Silicon hardware. It specifically addresses the needs of coding agents by employing paged SSD KV caching, allowing cache blocks to be retained on disk; thus, previously accessed prefixes can be swiftly retrieved across various requests and even after server restarts, negating the need for recalculation from the ground up. Consequently, the duration required to produce the first token in extensive contexts can drop dramatically, from a span of 30 to 90 seconds down to under five seconds following the initial interaction. The server skillfully handles multiple requests simultaneously through a constant batching approach using mlx-lm’s BatchGenerator, which improves overall generation throughput by preventing requests from queuing behind a single task. oMLX can serve a diverse array of models concurrently, including LLMs, vision-language models, embedding models, and rerankers, while efficiently managing memory limitations through LRU eviction. Additionally, it supports any MLX-format model available from Hugging Face, including Qwen, LLaMA, Mistral, Gemma, DeepSeek, MiniMax, and GLM, and has the capability to work with models stored in the regular Hugging Face cache, directories linked to LM Studio, or any custom storage solutions, thus providing a seamless experience for users. This adaptability in model integration not only enhances the functionality of oMLX but also significantly benefits developers and researchers, making it a practical tool in various AI applications. Overall, oMLX stands out as a robust solution for maximizing the potential of AI on macOS systems.
What is Yandex Cloud CDN?
Improve the speed at which your service delivers media assets by employing content caching across a network of globally positioned CDN servers. These worldwide CDN servers are designed to fetch, store, and deliver your content to users as required. To enhance load balancing and speed up content distribution, arrange servers that host duplicate content strategically. It is also essential to utilize content caching for both the CDN servers and user browsers, specify how long file copies should be stored, and prepare large files ahead of user requests. Within Yandex Cloud CDN, you can assess various metrics related to the amount of traffic you have both received and transmitted, along with monitoring the number of requests and errors over the past month, which provides valuable insights into your service's performance. This detailed analysis not only aids in identifying potential issues but also supports you in making well-informed choices for future enhancements to your service.
Integrations Supported
Anthropic
Claude Code
Cursor
DeepSeek
GLM-4.1V
Gemma
Gemma
GitHub
Hugging Face
JSON
Integrations Supported
Anthropic
Claude Code
Cursor
DeepSeek
GLM-4.1V
Gemma
Gemma
GitHub
Hugging Face
JSON
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
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
oMLX
Company Location
United States
Company Website
omlx.ai/
Company Facts
Organization Name
Yandex
Company Location
United Arab Emirates
Company Website
cloud.yandex.com/en/services/cdn