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Description

Gemini 3.7 Flash represents Google's most advanced model for coding and agents, exhibiting significant enhancements in software engineering, knowledge-intensive tasks, web design, and intricate business processes. It excels in debugging and resolving issues, showcasing greater accuracy in first-pass code creation and a refined ability to generate code that is ready for production. When applied to web development, this model produces more functional designs and fully-featured applications with fewer prompts, maintaining strong adherence to design principles derived from screenshots, images, or comprehensive design systems. In fields with high knowledge requirements, such as finance, law, and biosciences, it enhances reasoning capabilities, precision, and comprehension of complex documents. Additionally, Gemini 3.7 Flash demonstrates superior performance in automating real-world workflows and executing multimodal tasks, catering to a range of applications from interactive web experiences and data storytelling to robotics and the creation of dynamically generated 3D content. Overall, its versatility makes it a powerful tool for a variety of professional domains.

Description

Innovations in healthcare have the potential to transform lives and inspire hope, driven by a combination of scientific expertise, empathy, and human understanding. We are confident that artificial intelligence can play a significant role in this transformation through effective collaboration among researchers, healthcare providers, and the wider community. Today, we are thrilled to announce promising strides in these efforts, unveiling limited access to Google’s medical-focused large language model, Med-PaLM 2. In the upcoming weeks, this model will be made available for restricted testing to a select group of Google Cloud clients, allowing them to explore its applications and provide valuable feedback as we pursue safe and responsible methods of leveraging this technology. Med-PaLM 2 utilizes Google’s advanced LLMs, specifically tailored for the medical field, to enhance the accuracy and safety of responses to medical inquiries. Notably, Med-PaLM 2 achieved the distinction of being the first LLM to perform at an “expert” level on the MedQA dataset, which consists of questions modeled after the US Medical Licensing Examination (USMLE). This milestone reflects our commitment to advancing healthcare through innovative solutions and highlights the potential of AI in addressing complex medical challenges.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

C++
CSS
Cursor
Dart
Devin Desktop
Gemini 3.5 Flash
Gemini Enterprise
Gemini Enterprise Agent Platform Notebooks
Gemini Managed Agents
Google AI Studio
Google Antigravity
Google Cloud Platform
JetBrains Junie
OfoxAI
PowerShell
R
Ruby
Rust
Scala
Vercel AI Gateway

Integrations

C++
CSS
Cursor
Dart
Devin Desktop
Gemini 3.5 Flash
Gemini Enterprise
Gemini Enterprise Agent Platform Notebooks
Gemini Managed Agents
Google AI Studio
Google Antigravity
Google Cloud Platform
JetBrains Junie
OfoxAI
PowerShell
R
Ruby
Rust
Scala
Vercel AI Gateway

Pricing Details

$0.75 per 1M tokens (input)
$0.75/1M input and $3.75/1M output tokens
Free Trial
Free Version

Pricing Details

No price information available.
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

Google

Founded

1998

Country

United States

Website

google.com

Vendor Details

Company Name

Google Cloud

Country

United States

Website

cloud.google.com/blog/topics/healthcare-life-sciences/sharing-google-med-palm-2-medical-large-language-model

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