Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

MedGemma is an innovative suite of Gemma 3 variants specifically designed to excel in the analysis of medical texts and images. This resource empowers developers to expedite the creation of AI applications focused on healthcare. Currently, MedGemma offers two distinct variants: a multimodal version with 4 billion parameters and a text-only version featuring 27 billion parameters. The 4B version employs a SigLIP image encoder, which has been meticulously pre-trained on a wealth of anonymized medical data, such as chest X-rays, dermatological images, ophthalmological images, and histopathological slides. Complementing this, its language model component is trained on a wide array of medical datasets, including radiological images and various pathology visuals. MedGemma 4B can be accessed in both pre-trained versions, denoted by the suffix -pt, and instruction-tuned versions, marked by the suffix -it. For most applications, the instruction-tuned variant serves as the optimal foundation to build upon, making it particularly valuable for developers. Overall, MedGemma represents a significant advancement in the integration of AI within the medical field.

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

Hugging Face Yes 
Anthropic No 
Claude Code No 
DeepSeek No 
Dr7.ai Yes 
GLM-4.1V No 
Gemini Enterprise Agent Platform Yes 
Gemma No 
Gemma No 
Gemma 2 Yes 
Gemma 3 Yes 
Gemma 4 Yes 
GitHub No 
JSON No 
LM Studio No 
Llama No 
MiniMax No 
Model Context Protocol (MCP) No 
OpenAI No 
OpenClaw No 

Integrations

Hugging Face Yes 
Anthropic Yes 
Claude Code Yes 
DeepSeek Yes 
Dr7.ai No 
GLM-4.1V Yes 
Gemini Enterprise Agent Platform No 
Gemma Yes 
Gemma Yes 
Gemma 2 No 
Gemma 3 No 
Gemma 4 No 
GitHub Yes 
JSON Yes 
LM Studio Yes 
Llama Yes 
MiniMax Yes 
Model Context Protocol (MCP) Yes 
OpenAI Yes 
OpenClaw Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

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 Yes 
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 Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

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

Vendor Details

Company Name

Google DeepMind

Founded

2010

Country

United Kingdom

Website

deepmind.google/models/gemma/medgemma/

Vendor Details

Company Name

oMLX

Country

United States

Website

omlx.ai/

Product Features

Product Features

Alternatives

PaliGemma 2 Reviews

PaliGemma 2

Google

Alternatives

Run BiOS Reviews

Run BiOS

UltraSafe AI Inc.
CodeGemma Reviews

CodeGemma

Google
Photon Reviews

Photon

Moondream
Gemma Reviews

Gemma

Google
BaseRT Reviews

BaseRT

Base Compute
Macyou Reviews

Macyou

Macyou LLC