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

Ratings and Reviews 1 Rating

Total
features

Alternatives to Consider

  • LTX Reviews & Ratings
    182 Ratings
    Company Website
  • sellerboard Reviews & Ratings
    169 Ratings
  • Portfolio Manager Reviews & Ratings
    3 Ratings
    Company Website
  • SiteDocs Reviews & Ratings
    290 Ratings
    Company Website
  • CampaignTrackly Reviews & Ratings
    57 Ratings
    Company Website
  • optivalue.ai Reviews & Ratings
    4 Ratings
    Company Website
  • AddSearch Reviews & Ratings
    140 Ratings
    Company Website
  • Pensero Reviews & Ratings
    2 Ratings
    Company Website
  • Yeastar P-Series PBX System Reviews & Ratings
    116 Ratings
    Company Website
  • DeskTime Reviews & Ratings
    955 Ratings
    Company Website

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-Small?

Inkling-Small is an efficient multimodal AI model built to deliver strong reasoning and coding performance at a fraction of Inkling’s size. It is a Mixture-of-Experts transformer with 276 billion total parameters and 12 billion active parameters. The model was trained on NVIDIA GB300 NVL72 systems and is designed to combine high capability with more efficient inference. Inkling-Small supports native reasoning across text, images, and audio, allowing it to work across multimodal tasks without relying on separate encoders. Its context window supports up to one million tokens, making it useful for long-form reasoning, large-scale code understanding, document analysis, and agentic workflows. Users can adjust reasoning effort from minimal to extra high depending on whether they need faster responses or deeper computation. The model’s training process includes improved pre-training data, post-training with on-policy distillation from Inkling, and extended agentic coding reinforcement learning. These techniques helped Inkling-Small outperform its larger counterpart on reasoning and coding benchmarks. The model performs well in coding and tool-use harnesses and exceeds 80% on SWE-bench Verified. Its encoder-free architecture processes audio as dMel spectrograms and images as 40-by-40-pixel patches alongside text tokens. By combining efficient MoE design, one-million-token context, adjustable reasoning effort, multimodal processing, coding strength, and tool-use performance, Inkling-Small is designed for developers and teams that need capable AI with lower active compute requirements.

Media

Media

Integrations Supported

Claude Code
Hermes Agent
Kilo Code
Model Context Protocol (MCP)
OpenClaw
OpenRouter
Tinker
ZenMux

Integrations Supported

Claude Code
Hermes Agent
Kilo Code
Model Context Protocol (MCP)
OpenClaw
OpenRouter
Tinker
ZenMux

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

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/news/inkling-small/

Categories and Features

Popular Alternatives

GLM-5.2 Reviews & Ratings

GLM-5.2

Zhipu AI

Popular Alternatives

Kimi K3 Reviews & Ratings

Kimi K3

Moonshot AI
Qwen3.8-Max Reviews & Ratings

Qwen3.8-Max

Alibaba
Ling 2.6 Flash Reviews & Ratings

Ling 2.6 Flash

Ant Group
Inkling Reviews & Ratings

Inkling

Thinking Machines Lab