Average Ratings 1 Rating

Total
features

Average Ratings 1 Rating

Total
features

Description

Inkling-Small is an efficient Mixture-of-Experts transformer model built to provide performance comparable to Inkling while using a much smaller active parameter footprint. The model has 276 billion total parameters and 12 billion active parameters, making it designed for strong capability with more efficient compute usage. Inkling-Small was trained on NVIDIA GB300 NVL72 systems and supports native reasoning across text, images, and audio. It offers context windows of up to one million tokens, making it suitable for long documents, large codebases, multimodal context, and extended agent workflows. Users can set reasoning effort from minimal to extra high to control the balance between speed, cost, compute, and task complexity. The model benefits from improved pre-training data, post-training with on-policy distillation from Inkling, and extended agentic coding reinforcement learning. These improvements helped Inkling-Small surpass its larger counterpart on reasoning and coding benchmarks. Its encoder-free multimodal architecture processes audio as dMel spectrograms and images as 40-by-40-pixel patches alongside text tokens. By combining efficient MoE scaling, long-context reasoning, multimodal input, coding strength, and adjustable thinking effort, Inkling-Small is built for practical high-performance AI deployment.

Description

Qwen3.6-27B is an open-source, dense multimodal language model from the Qwen3.6 series, engineered to provide top-tier performance in areas such as coding, reasoning, and agent-driven workflows, all while maintaining an efficient parameter count of 27 billion. This model is recognized for its ability to outperform or compete closely with much larger counterparts on essential benchmarks, particularly excelling in agent-based coding tasks. It features dual operational modes—thinking and non-thinking—that enable it to effectively adapt its reasoning depth and response speed based on the specific requirements of each task. Additionally, it supports a variety of input types, including text, images, and video, showcasing its versatility. As part of the Qwen3.6 lineup, this model prioritizes practical usability, consistency, and the enhancement of developer productivity, reflecting advancements inspired by community insights and real-world application demands. Its innovative design not only responds to immediate user needs but also anticipates future trends in AI development.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud Model Studio No 
Cheaper Inference No 
Hugging Face No 
Model Context Protocol (MCP) Yes 
ModelScope No 
Ollama No 
OpenClaw No 
Python No 
Qwen No 
Qwen Studio No 
Qwen3.6 No 
Tinker Yes 

Integrations

Alibaba Cloud Model Studio Yes 
Cheaper Inference Yes 
Hugging Face Yes 
Model Context Protocol (MCP) No 
ModelScope Yes 
Ollama Yes 
OpenClaw Yes 
Python Yes 
Qwen Yes 
Qwen Studio Yes 
Qwen3.6 Yes 
Tinker No 

Pricing Details

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

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 Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
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

Thinking Machines Lab

Founded

2025

Country

United States

Website

thinkingmachines.ai/news/inkling-small/

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

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