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Description
Gemini 4 is Google’s upcoming next-generation AI model family and the future successor to its current Gemini 3.x lineup. Google has confirmed that it has started pre-training Gemini 4, describing it as its most ambitious pre-training run so far. The model has not been officially launched, so there are no public API endpoints, pricing details, model cards, benchmark results, or release dates available yet. Gemini 4 is expected to build on the direction of recent Gemini models, including stronger coding, reasoning, multimodal performance, computer use, and agentic workflow support. Google’s current Gemini releases already emphasize efficiency, lower latency, better tool use, and enterprise deployment, and Gemini 4 is likely to extend those priorities at a larger scale. The model may eventually support developers building AI agents, enterprise copilots, coding tools, research assistants, multimodal apps, and knowledge-work automation. It will likely play a role across Google AI Studio, the Gemini API, Gemini Enterprise, Google Cloud, and consumer-facing Gemini experiences once released. For now, Gemini 4 should be treated as a confirmed future model in training rather than an available product. By representing Google’s next major frontier model effort, Gemini 4 signals the company’s continued push toward more capable AI systems for developers, enterprises, and everyday users.
Description
Mercury 2.5 represents the pinnacle of production models from Inception, demonstrating a remarkable enhancement in quality compared to its predecessor, Mercury 2, all while upholding an impressive low-latency serving profile. It stands out as the most advanced diffusion language model currently available and is touted by Inception as the largest diffusion LLM ever developed. With a 40% boost in intelligence over Mercury 2, its performance aligns closely with that of cost-efficient frontier models like GPT-5.6 Luna (Low), Gemini 3.5 Flash-Lite, and Claude Haiku 4.5. The model boasts a generation speed of 1,107 tokens per second on commonly accessible NVIDIA GPUs and accommodates a generous 260K-token context window. Among its features are adjustable reasoning capabilities, simultaneous tool calls, and JSON that aligns with schemas. Specifically engineered for latency-sensitive tasks, it is well-suited for scenarios involving numerous model calls during a single interaction. In applications such as search agents and RAG pipelines, Mercury 2.5 excels in functions like planning, query rewriting, re-ranking, fact structuring, source summarization, and answer verification, all while ensuring rapid response times, making it an essential tool for developers seeking efficiency in their workflows.
API Access
Has API
API Access
Has API
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Pricing Details
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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
Founded
1998
Country
United States
Website
gemini.com
Vendor Details
Company Name
Inception
Country
United States
Website
www.inceptionlabs.ai/blog/introducing-mercury-2-5