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Description

Molmo 2 represents a cutting-edge suite of open vision-language models that come with completely accessible weights, training data, and code, thereby advancing the original Molmo series' capabilities in grounded image comprehension to encompass video and multiple image inputs. This evolution enables sophisticated video analysis, including pointing, tracking, dense captioning, and question-answering functionalities, all of which demonstrate robust spatial and temporal reasoning across frames. The suite consists of three distinct models: an 8 billion-parameter variant tailored for comprehensive video grounding and QA tasks, a 4 billion-parameter model that prioritizes efficiency, and a 7 billion-parameter model backed by Olmo, which features a fully open end-to-end architecture that includes the foundational language model. Notably, these new models surpass their predecessors on key benchmarks, setting unprecedented standards for open-model performance in image and video comprehension tasks. Furthermore, they often rival significantly larger proprietary systems while being trained on a much smaller dataset compared to similar closed models, showcasing their efficiency and effectiveness in the field. This impressive achievement marks a significant advancement in the accessibility and performance of AI-driven visual understanding technologies.

Description

Phi-4-mini-flash-reasoning is a 3.8 billion-parameter model that is part of Microsoft's Phi series, specifically designed for edge, mobile, and other environments with constrained resources where processing power, memory, and speed are limited. This innovative model features the SambaY hybrid decoder architecture, integrating Gated Memory Units (GMUs) with Mamba state-space and sliding-window attention layers, achieving up to ten times the throughput and a latency reduction of 2 to 3 times compared to its earlier versions without compromising on its ability to perform complex mathematical and logical reasoning. With a support for a context length of 64K tokens and being fine-tuned on high-quality synthetic datasets, it is particularly adept at handling long-context retrieval, reasoning tasks, and real-time inference, all manageable on a single GPU. Available through platforms such as Azure AI Foundry, NVIDIA API Catalog, and Hugging Face, Phi-4-mini-flash-reasoning empowers developers to create applications that are not only fast but also scalable and capable of intensive logical processing. This accessibility allows a broader range of developers to leverage its capabilities for innovative solutions.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Hugging Face Yes 
Ai2 OLMoE Yes 
Bluesky Yes 
Microsoft 365 Copilot No 
Microsoft Foundry No 
Microsoft Foundry Agent Service No 
NVIDIA DRIVE No 
Olmo 2 Yes 
Threads Yes 

Integrations

Hugging Face Yes 
Ai2 OLMoE No 
Bluesky No 
Microsoft 365 Copilot Yes 
Microsoft Foundry Yes 
Microsoft Foundry Agent Service Yes 
NVIDIA DRIVE Yes 
Olmo 2 No 
Threads 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 No 
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 Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

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

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Ai2

Founded

2014

Country

United States

Website

allenai.org/blog/molmo2

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/blog/reasoning-reimagined-introducing-phi-4-mini-flash-reasoning/

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