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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
Kimi K2 Thinking is a sophisticated open-source reasoning model created by Moonshot AI, specifically tailored for intricate, multi-step workflows where it effectively combines chain-of-thought reasoning with tool utilization across numerous sequential tasks. Employing a cutting-edge mixture-of-experts architecture, the model encompasses a staggering total of 1 trillion parameters, although only around 32 billion parameters are utilized during each inference, which enhances efficiency while retaining significant capability. It boasts a context window that can accommodate up to 256,000 tokens, allowing it to process exceptionally long inputs and reasoning sequences without sacrificing coherence. Additionally, it features native INT4 quantization, which significantly cuts down inference latency and memory consumption without compromising performance. Designed with agentic workflows in mind, Kimi K2 Thinking is capable of autonomously invoking external tools, orchestrating sequential logic steps—often involving around 200-300 tool calls in a single chain—and ensuring consistent reasoning throughout the process. Its robust architecture makes it an ideal solution for complex reasoning tasks that require both depth and efficiency.
API Access
Has API
Yes
API Access
Has API
No
Integrations
GPT-5
No
GPT-5.1 Pro
No
GPT-5.1 Thinking
No
GPT-5.2 Instant
No
GPT-5.2 Pro
No
GPT-5.2 Thinking
No
GPT-5.4 Pro
No
GPT-5.4 mini
No
GPT-5.4 nano
No
GPT-5.6 Luna
No
Integrations
GPT-5
Yes
GPT-5.1 Pro
Yes
GPT-5.1 Thinking
Yes
GPT-5.2 Instant
Yes
GPT-5.2 Pro
Yes
GPT-5.2 Thinking
Yes
GPT-5.4 Pro
Yes
GPT-5.4 mini
Yes
GPT-5.4 nano
Yes
GPT-5.6 Luna
Yes
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
Open source
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
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
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
Moonshot AI
Founded
2023
Country
United States
Website
moonshotai.github.io/Kimi-K2/thinking.html