Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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

Write a Review

Alternatives to Consider

  • LTX Reviews & Ratings
    4.4 out of 5 stars 182 Ratings
    Company Website for LTX
  • SiteDocs Reviews & Ratings
    4.8 out of 5 stars 290 Ratings
    Company Website for SiteDocs
  • Portfolio Manager Reviews & Ratings
    5.0 out of 5 stars 3 Ratings
    Company Website for Portfolio Manager
  • Elecard Boro Reviews & Ratings
    4.7 out of 5 stars 9 Ratings
    Company Website for Elecard Boro
  • optivalue.ai Reviews & Ratings
    5.0 out of 5 stars 4 Ratings
    Company Website for optivalue.ai
  • AddSearch Reviews & Ratings
    4.6 out of 5 stars 145 Ratings
    Company Website for AddSearch
  • Yeastar P-Series PBX System Reviews & Ratings
    4.8 out of 5 stars 116 Ratings
    Company Website for Yeastar P-Series PBX System
  • FinOpsly Reviews & Ratings
    4.7 out of 5 stars 3 Ratings
    Company Website for FinOpsly
  • TinyPNG Reviews & Ratings
    4.7 out of 5 stars 73 Ratings
    Company Website for TinyPNG
  • PBRS Power BI Reports Distribution Reviews & Ratings
    4.4 out of 5 stars 12 Ratings
    Company Website for PBRS Power BI Reports Distribution

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.

What is Inkling 2 Small?

Inkling 2 Small is an advanced multimodal large language model developed by Thinking Machines Lab to support autonomous coding, complex reasoning, visual understanding, and customizable AI applications. The model uses a sparse mixture-of-experts transformer architecture containing 594 billion total parameters and 17 billion active parameters, with 48 decoder layers and 384 specialized experts. Its architecture combines local and global attention mechanisms with a vision transformer that processes images alongside text within a shared representation. Inkling 2 Small supports a context window of up to one million tokens, making it suitable for analyzing extensive documents, large software repositories, and long-running agent workflows. Configurable reasoning effort enables users to adjust the computational resources devoted to individual tasks based on their complexity and performance requirements. Its agentic software engineering capabilities include generating code, debugging applications, implementing features, verifying changes, and operating development tools across extended workflows. The model can also create interactive websites, games, three-dimensional simulations, and visual applications while using image-based feedback to evaluate and improve its results. Advanced research capabilities allow autonomous agents to conduct machine learning experiments, optimize GPU kernels, evaluate training strategies, and iteratively refine technical solutions. Thinking Machines Lab trained the model using 8.4 trillion pretraining tokens and a large reinforcement learning process involving more than 17 million rollouts across coding, scientific reasoning, visual tasks, knowledge work, and tool use. Published evaluation results include 25.4% on FrontierCode 2.0, 72.1% on DeepSWE 1.1, 86.3% on SWE-Bench Pro v2 Hard, and an Artificial Analysis Intelligence Index score of 31.

Media

Media

Integrations Supported

Claude Code
Hermes Agent
Kilo Code
OpenClaw
OpenRouter
ZenMux

Integrations Supported

Model Context Protocol (MCP)
Tinker

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$0.30 per million input tokens
$0.30 per million input tokens, $0.03 per million cached input tokens, and $1.00 per million output tokens

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

Ant Group

Date Founded

2014

Company Location

China

Company Website

ant-ling.com

Company Facts

Organization Name

Thinking Machines Lab

Date Founded

2025

Company Location

United States

Company Website

thinkingmachines.ai/

Categories and Features

AI Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Vision Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

Popular Alternatives

GLM-5.2 Reviews & Ratings

GLM-5.2

Z.ai
5.0 out of 5 stars

Popular Alternatives

GPT-6 Luna Reviews & Ratings

GPT-6 Luna

OpenAI
5.0 out of 5 stars
Kimi K3 Reviews & Ratings

Kimi K3

Moonshot AI
5.0 out of 5 stars
Qwen3.8-Max Reviews & Ratings

Qwen3.8-Max

Alibaba
5.0 out of 5 stars
Kimi K3.1 Pro Reviews & Ratings

Kimi K3.1 Pro

Moonshot AI
5.0 out of 5 stars
Ling 2.6 Flash Reviews & Ratings

Ling 2.6 Flash

Ant Group
Inkling-Small Reviews & Ratings

Inkling-Small

Thinking Machines Lab
5.0 out of 5 stars