Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Inkling is Thinking Machines’ open-weights foundation model built for customization, multimodal reasoning, and agentic AI workflows. The model uses a Mixture-of-Experts architecture with 975 billion total parameters and 41 billion active parameters, making it large in capacity while activating only a subset of experts per token. Inkling supports up to a 1 million token context window and was pretrained on 45 trillion tokens spanning text, images, audio, and video. It is designed as a broad generalist model with strengths across coding, reasoning, instruction following, factuality, tool use, vision, audio understanding, forecasting, and safety. Developers can tune its thinking effort to trade off latency, cost, and performance, which is useful for production systems that need efficient reasoning at scale. Inkling can be fine-tuned on Tinker, tested in the Inkling Playground, and deployed through partners such as TogetherAI, Fireworks, Modal, Databricks, Baseten, vLLM, SGLang, llama.cpp, and Hugging Face transformers. The model can generate applications, operate tools, create styled artifacts, reason over visual and audio inputs, and support long refinement loops for collaborative work. Thinking Machines also previewed Inkling-Small, a lighter Mixture-of-Experts model with 276 billion total parameters and 12 billion active parameters for lower-cost and lower-latency workloads. By combining open weights, multimodal training, agentic capabilities, efficient reasoning, and fine-tuning support, Inkling gives builders a flexible AI foundation for specialized products and workflows.

Description

SubQ is an advanced large language model created by Subquadratic to handle complex long-context reasoning tasks. It supports up to 12 million tokens in a single input, making it capable of analyzing entire repositories, extended conversation histories, and large datasets without losing context. The model is built on a sub-quadratic sparse-attention architecture that focuses computational resources on the most relevant data relationships. This design significantly reduces processing requirements compared to traditional transformer models while maintaining strong performance. SubQ is particularly useful for software engineering, coding workflows, and long-context retrieval tasks. It enables developers and teams to process large amounts of information in a single operation instead of splitting tasks into smaller parts. The model offers fast processing speeds and operates at a fraction of the cost of many competing solutions. It is available through API access, allowing integration into enterprise systems and developer tools. SubQ can also be used as a layer within coding agents to improve code exploration and analysis. Its compatibility with existing development environments makes it easier to adopt. With its efficient architecture and large context window, it helps teams work with complex data more effectively.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Claude Code No 
Model Context Protocol (MCP) Yes 
OpenAI No 
OpenAI Codex No 
SubQ 1.1 Small No 
Tinker Yes 

Integrations

Claude Code Yes 
Model Context Protocol (MCP) No 
OpenAI Yes 
OpenAI Codex Yes 
SubQ 1.1 Small Yes 
Tinker No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
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 No 

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

Subquadratic

Founded

2026

Country

United States

Website

subq.ai/

Alternatives

Alternatives

Inkling Reviews

Inkling

Thinking Machines Lab
GPT-5.5 Reviews

GPT-5.5

OpenAI
Inkling-Small Reviews

Inkling-Small

Thinking Machines Lab
SubQ 1.1 Small Reviews

SubQ 1.1 Small

Subquadratic
Claude Mythos Reviews

Claude Mythos

Anthropic