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What is Qwen Code?

Qwen3-Coder is a sophisticated coding model available in multiple sizes, with its standout 480B-parameter Mixture-of-Experts variant (featuring 35B active parameters) capable of handling 256K-token contexts that can be expanded to 1M, showcasing superior performance in Agentic Coding, Browser-Use, and Tool-Use tasks, effectively competing with Claude Sonnet 4. The model undergoes a pre-training phase that utilizes a staggering 7.5 trillion tokens, of which 70% consist of code, alongside synthetic data improved from Qwen2.5-Coder, thereby boosting its coding proficiency and overall functionality. Its post-training phase benefits from extensive execution-driven reinforcement learning across 20,000 parallel environments, allowing it to tackle complex multi-turn software engineering tasks like SWE-Bench Verified without requiring test-time scaling. Furthermore, the open-source Qwen Code CLI, adapted from Gemini Code, enables the implementation of Qwen3-Coder in agentic workflows through customized prompts and function calling protocols, ensuring seamless integration with platforms like Node.js and OpenAI SDKs. This blend of powerful features and versatile accessibility makes Qwen3-Coder an invaluable asset for developers aiming to elevate their coding endeavors and streamline their workflows effectively. As a result, it serves as a pivotal resource in the rapidly evolving landscape of programming tools.

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

Alibaba AI Coding Plan
Claude Fable 5
Claude Mythos 5
Claude Opus 4.1
Claude Opus 4.5
Claude Opus 4.6
Claude Opus 4.7
Claude Opus 4.8
Claude Opus 5
Claude Sonnet 4
Claude Sonnet 4.5
Claude Sonnet 4.6
Model Context Protocol (MCP)
Node.js
OpenAI
OpenSpec
Qwen2.5
Qwen3.7-Max
Qwen3.8 Max
Tinker

Integrations Supported

Alibaba AI Coding Plan
Claude Fable 5
Claude Mythos 5
Claude Opus 4.1
Claude Opus 4.5
Claude Opus 4.6
Claude Opus 4.7
Claude Opus 4.8
Claude Opus 5
Claude Sonnet 4
Claude Sonnet 4.5
Claude Sonnet 4.6
Model Context Protocol (MCP)
Node.js
OpenAI
OpenSpec
Qwen2.5
Qwen3.7-Max
Qwen3.8 Max
Tinker

API Availability

Has API

API Availability

Has API

Pricing Information

Free
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

Qwen

Date Founded

2023

Company Location

China

Company Website

github.com/QwenLM/qwen-code

Company Facts

Organization Name

Thinking Machines Lab

Date Founded

2025

Company Location

United States

Company Website

thinkingmachines.ai/news/inkling-small/

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