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What is Muse Spark 1.3?

Muse Spark 1.3 showcases a sophisticated AI model that significantly enhances its abilities for both agentic and programming tasks, thereby increasing its intelligence and practical utility for daily use. It is particularly adept at sustaining concentration on lengthy projects through active user collaboration, all while skillfully orchestrating multiple workflows within a cohesive thread. When confronted with an open-ended objective, the model efficiently harnesses tools to derive context from chaotic or conflicting data, addresses strategy gaps, monitors its learning trajectory, and ultimately produces a polished final outcome. In instances where prompts are vague, it takes the initiative to request clarification, seeks help when obstacles arise, and verifies its next steps before making critical decisions. The model exhibits exceptional dependability in adhering to complex, lengthy instructions, ensuring that intricate requirements are consistently honored throughout multifaceted tasks without overlooking essential constraints or deviating from the intended workflow. Furthermore, its advanced multitasking abilities allow it to effectively match incoming requests to the relevant tasks, even when users make interjections or alter the focus of prior inquiries, resulting in a fluid user experience. Consequently, Muse Spark 1.3 stands out as a highly adaptable tool suitable for diverse applications, making it a valuable asset across various fields.

What is Ling 3.0 Tiny?

Ling 3.0 Tiny is an advanced reasoning model with open weights, consisting of 7.9 billion parameters in total and 1.3 billion that are active, while boasting a remarkable context window of 262,000 tokens. Utilizing a mixture-of-experts architecture, it expands the open-weights Pareto frontier in intelligence relative to its active parameters, all while maintaining a compact size suitable for deployment in various settings. With a score of 25 on the Artificial Analysis Intelligence Index, it rivals gpt-oss-120b, which has a score of 24, even though it uses 15 times fewer total parameters and 4 times fewer active parameters. This exceptional efficiency in parameters comes with a cost, as it demands a hefty 213 million output tokens to finalize the Intelligence Index evaluation. Moreover, Ling 3.0 Tiny shows significant progress in mitigating hallucination rates when compared to Ling-mini-2.0; it boosts its AA-Omniscience score by an impressive 59 points while maintaining consistent accuracy. Rather than resorting to random guesses in uncertain scenarios, the model opted to attempt only 37% of the posed questions during assessment, which resulted in a drastically lowered hallucination rate of 30%, a substantial improvement from the previous generation's staggering 96%. This strategic decision not only underscores the model's enhanced reasoning abilities but also emphasizes its potential for practical applications in the real world. Overall, Ling 3.0 Tiny exemplifies a significant step forward in the development of efficient and reliable AI models.

Media

Media

Integrations Supported

Claude Code
Hermes Agent
OpenClaw
C
Cheaper Inference
Go
Instagram
Java
JavaScript
Kubernetes
LangChain
Meta AI
Model Context Protocol (MCP)
Muse Image
Objective-C
OpenAI Codex
OpenCode
Rust
Solidity
Vercel AI SDK

Integrations Supported

Claude Code
Hermes Agent
OpenClaw

API Availability

Has API

API Availability

Pricing Information

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

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

meta.ai/

Company Facts

Organization Name

Ant Group

Date Founded

2014

Company Location

China

Company Website

ant-ling.com

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Models

Not specified

Small Language Models

Not specified

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