DataGemmaGoogle
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InklingThinking Machines Lab
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Related Products
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About
DataGemma represents a pioneering effort by Google to enhance the accuracy and reliability of large language models (LLMs) when dealing with statistical and numerical data. Launched as a set of open models, DataGemma leverages Google's Data Commons, a vast repository of public statistical data—to ground its responses in real-world facts. This initiative employs two innovative approaches: Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG). The RIG method integrates real-time data checks during the generation process to ensure factual accuracy, while RAG retrieves relevant information before generating responses, thereby reducing the likelihood of AI hallucinations. By doing so, DataGemma aims to provide users with more trustworthy and factually grounded answers, marking a significant step towards mitigating the issue of misinformation in AI-generated content.
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About
Inkling is an open-weights multimodal AI model from Thinking Machines designed as a customizable foundation model for developers, researchers, and enterprises. The model is a Mixture-of-Experts transformer with 975 billion total parameters, 41 billion active parameters, and support for context windows up to 1 million tokens. Inkling was trained from scratch on text, images, audio, and video, giving it native capabilities across reasoning, coding, agentic tool use, vision, audio, factuality, and instruction following. It is built with controllable thinking effort so users can balance performance, latency, and token efficiency for different workloads. The model is available for fine-tuning on Tinker, with playground access, API availability through ecosystem partners, and full weights published on Hugging Face. Built for customization, Inkling gives teams an open-weights base model for building domain-specific AI systems, multimodal agents, coding workflows, research tools, and more.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
AI developers in need of a tool to reduce AI hallucination by anchoring LLMs in real-world statistical information
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Audience
AI developers, researchers, model fine-tuning teams, enterprise AI groups, agent builders, coding tool makers, multimodal AI teams, infrastructure providers, and organizations that need open-weights models for customization, long-context reasoning, vision, audio, tool use, and specialized AI applications
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Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
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Online
Not Supported
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API
Offers API
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API
Offers API
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Screenshots and Videos |
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Pricing
No information available.
Free Version
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Free Trial
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Pricing
Free
Free Version
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Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
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Live Online
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In Person
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Training
Documentation
Supported
Webinars
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Live Online
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In Person
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Company InformationGoogle
Founded: 1994
United States
blog.google/technology/ai/google-datagemma-ai-llm/
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Company InformationThinking Machines Lab
Founded: 2025
United States
thinkingmachines.ai/
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Categories |
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Integrations
Gemini
Supported
Gemini 1.5 Flash
Supported
Gemini 1.5 Pro
Supported
Gemini 2.0
Supported
Gemini 2.0 Flash
Supported
Gemini Enterprise
Supported
Gemini Nano
Supported
Gemini Pro
Supported
Google AI Plus
Supported
Model Context Protocol (MCP)
Not Supported
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Integrations
Gemini
Not Supported
Gemini 1.5 Flash
Not Supported
Gemini 1.5 Pro
Not Supported
Gemini 2.0
Not Supported
Gemini 2.0 Flash
Not Supported
Gemini Enterprise
Not Supported
Gemini Nano
Not Supported
Gemini Pro
Not Supported
Google AI Plus
Not Supported
Model Context Protocol (MCP)
Supported
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