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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

NativeMind serves as a completely open-source AI assistant that operates directly within your browser through Ollama integration, maintaining total privacy by refraining from sending any data to external servers. All processes, including model inference and prompt handling, take place locally, which eliminates concerns about syncing, logging, or data leaks. Users can effortlessly transition between various powerful open models like DeepSeek, Qwen, Llama, Gemma, and Mistral, requiring no extra configurations, while taking advantage of native browser capabilities to enhance their workflows. Additionally, NativeMind provides efficient webpage summarization; it maintains ongoing, context-aware conversations across multiple tabs; offers local web searches that can answer questions straight from the page; and delivers immersive translations that keep the original format intact. Designed with an emphasis on both efficiency and security, this extension is fully auditable and supported by the community, ensuring enterprise-level performance suitable for real-world applications without the risk of vendor lock-in or obscure telemetry. Moreover, the user-friendly interface and seamless integration make it an appealing choice for those seeking a reliable AI assistant that prioritizes their privacy.

Description

oMLX is an MLX server specifically designed for macOS, enhancing the efficiency and speed of local AI operations on Apple Silicon. It caters to the functional dynamics of coding agents by implementing paged SSD KV caching, which enables the persistence of cache blocks on disk; this means that previously accessed prefixes can be retrieved quickly across different requests and even after server restarts, thereby eliminating the need to recompute them from scratch. As a result, the time taken to generate the first token in lengthy contexts can be significantly reduced, dropping from a range of 30 to 90 seconds down to less than five seconds after the initial interaction. The server adeptly manages simultaneous requests through a continuous batching mechanism via mlx-lm’s BatchGenerator, which enhances overall generation throughput without requiring requests to queue up behind a single task. oMLX is capable of simultaneously serving a variety of models, including LLMs, vision-language models, embedding models, and rerankers, utilizing LRU eviction to manage memory constraints effectively. Furthermore, it is compatible with any MLX-format model sourced from Hugging Face, such as Qwen, LLaMA, Mistral, Gemma, DeepSeek, MiniMax, and GLM, and can also utilize models that are already present in the standard Hugging Face cache, directories associated with LM Studio, or any custom storage locations, ensuring a versatile user experience. This flexibility in model integration enhances the overall usability and practicality of oMLX for developers and researchers alike.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

DeepSeek Yes 
Gemma Yes 
Llama Yes 
Mistral AI Yes 
Qwen Yes 
Anthropic No 
Claude Code No 
Cursor No 
GLM-4.1V No 
Gemma No 
GitHub No 
JSON No 
LM Studio No 
Medium Yes 
MiniMax No 
Model Context Protocol (MCP) No 
OpenAI No 
Phi-3 Yes 
Phi-4 Yes 
Python No 

Integrations

DeepSeek Yes 
Gemma Yes 
Llama Yes 
Mistral AI Yes 
Qwen Yes 
Anthropic Yes 
Claude Code Yes 
Cursor Yes 
GLM-4.1V Yes 
Gemma Yes 
GitHub Yes 
JSON Yes 
LM Studio Yes 
Medium No 
MiniMax Yes 
Model Context Protocol (MCP) Yes 
OpenAI Yes 
Phi-3 No 
Phi-4 No 
Python Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac Yes 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

NativeMind

Country

United States

Website

nativemind.app/

Vendor Details

Company Name

oMLX

Country

United States

Website

omlx.ai/

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Product Features

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