Ratings and Reviews 1 Rating

Total
ease
features
design
support

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Gemini Enterprise Agent Platform Reviews & Ratings
    999 Ratings
    Company Website
  • LTX Reviews & Ratings
    182 Ratings
    Company Website
  • LM-Kit.NET Reviews & Ratings
    29 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    40 Ratings
    Company Website
  • TIMi Reviews & Ratings
    68 Ratings
    Company Website
  • Evertune Reviews & Ratings
    1 Rating
    Company Website
  • Google Cloud Platform Reviews & Ratings
    61,049 Ratings
    Company Website
  • Admin By Request Endpoint Privilege Management Reviews & Ratings
    105 Ratings
    Company Website
  • 800.com Reviews & Ratings
    2,381 Ratings
    Company Website
  • Superfiliate Reviews & Ratings
    49 Ratings
    Company Website

What is Muse Spark 1.1?

Muse Spark 1.1 is an advanced multimodal reasoning model from Meta Superintelligence Labs built for agentic work, coding, computer use, tool calling, and multimodal understanding. It is a major upgrade from Muse Spark and is designed to push the performance-efficiency frontier for AI systems that need to plan, reason, act, and coordinate across complex workflows. The model can operate across external apps, native tools, MCP servers, custom skills, browsers, scripts, images, videos, PDFs, audio, and developer environments. Muse Spark 1.1 is especially strong in agentic orchestration, where it can gather context, make plans, delegate work to parallel subagents, and manage execution across multiple steps. As a subagent, it can follow a defined role, use available tools appropriately, and escalate back to a main agent when needed. Its 1 million token context window helps it remember past actions, retrieve information from earlier in a project, and compact long sessions while keeping important details available for later work. For computer-use tasks, Muse Spark 1.1 can navigate unfamiliar interfaces, adapt to changing requirements, and choose whether to click through an interface or write scripts when automation is faster. In software engineering, the model can diagnose complex bugs, implement new features, perform large code migrations, build web applications, inspect screenshots, trace issues to code, and validate fixes. Its multimodal capabilities allow it to inspect visual and audio information, generate detailed image and video captions, create visual-to-code artifacts, and combine perception with action in practical workflows. Developers can access Muse Spark 1.1 through Meta’s new Model API public preview, and everyday users can try it in Thinking mode in the Meta AI app.

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
Bash
Continue
Facebook Messenger
Go
Java
JavaScript
Kotlin
Kubernetes
Model Context Protocol (MCP)
Muse Spark
Muse Video
PHP
Python
Ruby
Rust
WhatsApp
XML

Integrations Supported

Claude Code
Hermes Agent
OpenClaw

API Availability

Has API

API Availability

Pricing Information

$1.25 per 1M tokens (input)
$1.25 per million tokens in input, and $4.25 per million tokens of output
Free Trial Offered?

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

Popular Alternatives

GPT-5.6 Sol Reviews & Ratings

GPT-5.6 Sol

OpenAI

Popular Alternatives

GLM-5.2 Reviews & Ratings

GLM-5.2

Z.ai
Grok 4.6 Reviews & Ratings

Grok 4.6

SpaceXAI
Kimi K3 Reviews & Ratings

Kimi K3

Moonshot AI
Claude Opus 5 Reviews & Ratings

Claude Opus 5

Anthropic
Qwen3.8-Max Reviews & Ratings

Qwen3.8-Max

Alibaba
Ling 2.6 Flash Reviews & Ratings

Ling 2.6 Flash

Ant Group