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Average Ratings 0 Ratings
Description
Gemini 4 Pro is the expected high-capability model in Google's developing Gemini 4 generation, but Google has not yet formally announced a model carrying the Gemini 4 Pro name. Google confirmed in July 2026 that it had begun pre-training Gemini 4 as part of what was described as its most ambitious model training effort to date. By September, Google DeepMind leadership said Gemini 4 had advanced into its refinement stage and that the team was working toward releasing an early post-training version as soon as possible. Gemini 4 follows a series of Gemini 3.x models spanning general-purpose, Flash, Live, transcription, and specialized cybersecurity workloads. Google's Pro models are generally designed for higher-complexity reasoning and coding tasks, while its Flash models emphasize lower latency, efficiency, and production-scale economics. Gemini's broader platform already supports multimodal interaction, coding, tool use, connected applications, computer-use capabilities, and agentic experiences across Google products. Google has increasingly emphasized agents that can take actions and complete multi-step workflows rather than limiting Gemini to conversational responses. Specific benchmark scores, context limits, token pricing, supported modalities, and API details have not yet been published for Gemini 4 Pro. Reports claiming detailed Gemini 4 Pro specifications ahead of launch remain unconfirmed and should not be treated as official product information.
Description
Large language models, often requiring extensive computational resources for training over long periods, have demonstrated impressive proficiency in zero- and few-shot learning tasks. Due to the high investment needed for their development, replicating these models poses a significant challenge for many researchers. Furthermore, access to the few models available via API is limited, as users cannot obtain the complete model weights, complicating academic exploration. In response to this, we introduce Open Pre-trained Transformers (OPT), a collection of decoder-only pre-trained transformers ranging from 125 million to 175 billion parameters, which we intend to share comprehensively and responsibly with interested scholars. Our findings indicate that OPT-175B exhibits performance on par with GPT-3, yet it is developed with only one-seventh of the carbon emissions required for GPT-3's training. Additionally, we will provide a detailed logbook that outlines the infrastructure hurdles we encountered throughout the project, as well as code to facilitate experimentation with all released models, ensuring that researchers have the tools they need to explore this technology further.
API Access
Has API
Yes
API Access
Has API
No
Screenshots View All
No images available
Screenshots View All
No images available
Integrations
C#
Yes
CSS
Yes
Cursor
Yes
Dart
Yes
Gemini 3.5 Flash
Yes
Gemini 3.5 Flash-Lite
Yes
Gemini 3.8 Live
Yes
Gemini Spark
Yes
Google AI Mode
Yes
Google AI Overviews
Yes
Integrations
C#
No
CSS
No
Cursor
No
Dart
No
Gemini 3.5 Flash
No
Gemini 3.5 Flash-Lite
No
Gemini 3.8 Live
No
Gemini Spark
No
Google AI Mode
No
Google AI Overviews
No
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
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
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
No
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
Founded
1998
Country
United States
Website
gemini.com
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
www.meta.com