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Description

Ling 3.0 Tiny is a reasoning model featuring open weights, comprising 7.9 billion total parameters and 1.3 billion active parameters, alongside a substantial context window of 262,000 tokens. Leveraging a mixture-of-experts architecture, it pushes the boundaries of the open-weights Pareto frontier in terms of intelligence relative to active parameters, while being compact enough for local deployment in various environments. Scoring 25 on the Artificial Analysis Intelligence Index, it stands on par with gpt-oss-120b, which scores 24, despite utilizing 15 times fewer total parameters and 4 times fewer active parameters. This impressive parameter efficiency does come with a trade-off, as it requires a significant 213 million output tokens to complete the Intelligence Index evaluation. In addition, Ling 3.0 Tiny exhibits noteworthy advancements in reducing hallucination tendencies compared to Ling-mini-2.0; it enhances its AA-Omniscience score by 59 points while keeping accuracy levels consistent. Notably, rather than making random guesses in uncertain situations, the model chose to attempt only 37% of the questions during evaluation, leading to a markedly reduced hallucination rate of 30%, a significant improvement over the previous generation's 96%. This strategic approach not only demonstrates the model's improved reasoning capabilities but also highlights its potential for more reliable real-world applications.

Description

Muse Spark 1.3 represents an advanced AI model that has enhanced capabilities for both agentic and coding tasks, making it more intelligent and practical for use in everyday applications. It excels in maintaining focus on extended tasks through active collaboration with users while efficiently managing various workflows within a single, continuous thread. When faced with an open-ended goal, the model adeptly utilizes tools to create context from disorganized or contradictory information, rectify any gaps in its strategy, track its learning progress, and ultimately generate a final product. In situations where prompts lack clarity, it is proactive in seeking clarification, asking for assistance when it encounters obstacles, and confirming its actions before proceeding with significant decisions. The model demonstrates a high level of reliability in following intricate, long-form instructions, ensuring that detailed requirements are maintained throughout complex, multi-step tasks without losing critical constraints or deviating from the desired workflow. With its enhanced multitasking capabilities, it effectively aligns incoming prompts with the appropriate tasks, even in cases where users interject or shift the focus of previous requests, allowing for a seamless user experience. This makes Muse Spark 1.3 a versatile tool for a wide range of applications.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Claude Code Yes 
Hermes Agent Yes 
OpenClaw Yes 
Bash No 
C No 
Continue No 
Dart No 
Go No 
JavaScript No 
Model Context Protocol (MCP) No 
Muse Image No 
Muse Spark No 
Muse Video No 
Objective-C No 
Odysseus No 
OpenAI Agents SDK No 
OpenAI Codex No 
PHP No 
Scala No 
WhatsApp No 

Integrations

Claude Code Yes 
Hermes Agent Yes 
OpenClaw Yes 
Bash Yes 
C Yes 
Continue Yes 
Dart Yes 
Go Yes 
JavaScript Yes 
Model Context Protocol (MCP) Yes 
Muse Image Yes 
Muse Spark Yes 
Muse Video Yes 
Objective-C Yes 
Odysseus Yes 
OpenAI Agents SDK Yes 
OpenAI Codex Yes 
PHP Yes 
Scala Yes 
WhatsApp Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$1.25 per 1M tokens (input)
Input: $1.25 per 1M tokens
Output: $4.25 per 1M tokens
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 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

Ant Group

Founded

2014

Country

China

Website

ant-ling.com

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

meta.ai/

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