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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Kimi K2.5 is a powerful multimodal AI model built to handle complex reasoning, coding, and visual understanding at scale. It supports both text and image or video inputs, enabling developers to build applications that go beyond traditional language-only models. As Kimi’s most advanced model to date, it delivers open-source state-of-the-art performance across agent tasks, software development, and general intelligence benchmarks. The model supports an ultra-long 256K context window, making it ideal for large codebases, long documents, and multi-turn conversations. Kimi K2.5 includes a long-thinking mode that excels at logical reasoning, mathematics, and structured problem solving. It integrates seamlessly with existing workflows through full compatibility with the OpenAI SDK and API format. Developers can use Kimi K2.5 for chat, tool calling, file-based Q&A, and multimodal analysis. Built-in support for streaming, partial mode, and web search expands its flexibility. With predictable pricing and enterprise-ready capabilities, Kimi K2.5 is designed for scalable AI development.

Description

Qwen2.5-VL-32B represents an advanced AI model specifically crafted for multimodal endeavors, showcasing exceptional skills in reasoning related to both text and images. This iteration enhances the previous Qwen2.5-VL series, resulting in responses that are not only of higher quality but also more aligned with human-like formatting. The model demonstrates remarkable proficiency in mathematical reasoning, nuanced image comprehension, and intricate multi-step reasoning challenges, such as those encountered in benchmarks like MathVista and MMMU. Its performance has been validated through comparisons with competing models, often surpassing even the larger Qwen2-VL-72B in specific tasks. Furthermore, with its refined capabilities in image analysis and visual logic deduction, Qwen2.5-VL-32B offers thorough and precise evaluations of visual content, enabling it to generate insightful responses from complex visual stimuli. This model has been meticulously optimized for both textual and visual tasks, making it exceptionally well-suited for scenarios that demand advanced reasoning and understanding across various forms of media, thus expanding its potential applications even further.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

APIFree Yes 
AiAssistWorks Yes 
Alibaba AI Coding Plan Yes 
Brokk Yes 
Cherry Studio Yes 
Claw Code Yes 
EaseMate AI Yes 
Kimi Code Yes 
Kimi Work Yes 
NVIDIA TensorRT Yes 
Nebius Token Factory Yes 
Oh My OpenAgent Yes 
Okara Yes 
Ollama Yes 
OpenClaw Yes 
Oxlo.ai Yes 
Rapid Claw Yes 
Shiori Yes 
SiliconFlow Yes 
ZooClaw Yes 

Integrations

APIFree No 
AiAssistWorks No 
Alibaba AI Coding Plan No 
Brokk No 
Cherry Studio No 
Claw Code No 
EaseMate AI No 
Kimi Code No 
Kimi Work No 
NVIDIA TensorRT No 
Nebius Token Factory No 
Oh My OpenAgent No 
Okara No 
Ollama No 
OpenClaw No 
Oxlo.ai No 
Rapid Claw No 
Shiori No 
SiliconFlow No 
ZooClaw No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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 No 
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 No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Moonshot AI

Founded

2023

Country

China

Website

platform.moonshot.ai/

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwenlm.github.io/blog/qwen2.5-vl-32b/

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