Inkling-Small
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Description
Inkling 2 Small is a general-purpose multimodal AI model developed by Thinking Machines Lab for software engineering, advanced reasoning, visual analysis, and autonomous agent applications. The model features a sparse mixture-of-experts architecture containing 594 billion total parameters, with approximately 17 billion parameters activated during inference. Its one-million-token context window supports processing large documents, software repositories, extended conversations, and complex collections of information. Inkling 2 Small accepts text and image inputs and generates text outputs, enabling visual reasoning, programming assistance, document analysis, and multimodal problem-solving. Its agentic coding capabilities support autonomous software development, code debugging, repository modifications, application creation, and verification of completed engineering tasks. The model can also perform extended research workflows involving machine learning experimentation, GPU kernel optimization, data analysis, and iterative scientific problem-solving. Configurable reasoning effort allows users to balance response speed and computational resources against the complexity of individual tasks. Thinking Machines Lab reports benchmark scores of 25.4% on FrontierCode 2.0, 72.1% on DeepSWE 1.1, and 86.3% on SWE-Bench Pro v2 Hard. Inkling 2 Small is available for inference and fine-tuning through Tinker, with model weights scheduled for release under the Apache 2.0 license after additional safety evaluations.
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.
API Access
Has API
Yes
API Access
Has API
Yes
Pricing Details
$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
Free Trial
No
Free Version
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
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
No
iPad App
No
Android App
No
Windows
No
Mac
No
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/
Vendor Details
Company Name
Thinking Machines Lab
Founded
2025
Country
United States
Website
thinkingmachines.ai/news/inkling-small/