Average Ratings 1 Rating
Average Ratings 0 Ratings
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
NVIDIA Alpamayo 2 Super stands as a pioneering open model tailored for robotaxis and autonomous vehicles, designed to navigate rare and intricate driving scenarios while generating decisions that developers can analyze, verify, and rely upon. Utilizing the foundations of NVIDIA Cosmos 3 Super Reasoner and enhanced through reinforcement learning, it merges commercial accessibility with the ability to handle multiple tasks related to autonomous driving. The model comprehensively analyzes full-surround camera input, integrating perspectives from the front, sides, and rear to adeptly manage lane changes, merges, unprotected turns, and complex intersections. In addressing each driving scenario, it can produce a planned trajectory for the vehicle, a chain-of-causation that elucidates the decision-making process, a meta-action such as yielding or stopping, and reasoning auto-labels for both training and validation purposes, along with visual question-answering outputs anchored in specific image regions. These interconnected outputs facilitate the correlation between the model's observations and the actions it undertakes, thereby enhancing transparency in autonomous decision-making. Additionally, this functionality supports developers in refining and optimizing the model's performance in real-world applications.
API Access
Has API
API Access
Has API
Integrations
Model Context Protocol (MCP)
Tinker
Pricing Details
$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Thinking Machines Lab
Founded
2025
Country
United States
Website
thinkingmachines.ai/news/inkling-small/
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
nvidia.com