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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 Lucebox?
Lucebox is an all-in-one computer tailored for running local AI models and agents with optimal efficiency. Its unique enclosure contains a Ryzen AI MAX+ 395 processor paired with an impressive 128GB of unified LPDDR5X memory and an RTX 3090 graphics card, which collaborate seamlessly through a meticulously tuned open-source inference engine designed specifically for this hardware setup.
The architecture's design plays a crucial role in delivering outstanding performance. The abundant 128GB of unified memory efficiently accommodates large models, while the high-bandwidth VRAM of the RTX 3090 acts as a swift access layer. Utilizing advanced techniques such as speculative decoding (DFlash) and speculative prefill (PFlash), these two memory systems are interconnected, resulting in inference speeds that can be as much as ten times quicker than llama.cpp operating on identical hardware. This remarkable capability allows it to surpass competitors like the Mac Studio and DGX Spark, all while maintaining a far more budget-friendly price point. In addition, the combination of cutting-edge hardware and software enhancements firmly establishes Lucebox as a prominent contender in the realm of local AI computing, appealing to developers and enthusiasts alike.
Media
No images available
Integrations Supported
Anthropic
Claude Code
Cursor
DeepSeek
GLM-4.1V
Gemma
Gemma
GitHub
Hugging Face
JSON
API Availability
Has API
API Availability
Pricing Information
Pricing not provided
Pricing Information
$4,900 - One time payment
Supported Platforms
Mac
Supported Platforms
Linux
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
Company Facts
Organization Name
oMLX
Company Location
United States
Company Website
omlx.ai/
Company Facts
Organization Name
Lucebox
Date Founded
2026
Company Location
United States
Company Website
www.lucebox.com
Categories and Features
AI Inference
Not specified
Categories and Features
Hardware
Not specified