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
Lumen Outpost represents Cosine’s refined post-trained coding model, evaluated against its foundational model Kimi K2.6, along with GPT-5.5, GPT-5.4, and Gemini 3.1 Pro, specifically focusing on intricate, long-term coding assignments across 13 different programming languages. This model is designed not only for precision in coding but also to enhance key behavioral indicators vital in engineering processes, such as agent initiative, strategic planning, scope management, action coherence, succinct updates, and effective communication. According to Cosine’s benchmark analysis, the specialized post-training significantly elevated the base model's performance, with Lumen Outpost surpassing Kimi K2.6 in tests like Niche-Bench, Slop-Bench, Vibe-Bench, as well as in terms of cost efficiency for successful task completion. In the Niche-Bench assessment, which evaluates niche, legacy, and environmentally constrained programming languages, Lumen Outpost attained a score of 53.9% and excelled or equaled performance in 9 out of the 13 languages evaluated, demonstrating marked improvements particularly in Fortran, ABAP, Java, and Rust. The impressive results symbolize a significant leap in the practical application of coding models in real-world scenarios, underscoring the effectiveness of targeted training methodologies.
API Access
Has API
Yes
API Access
Has API
No
Integrations
ABAP
No
Fortran
No
Java
No
Model Context Protocol (MCP)
Yes
Rust
No
Tinker
Yes
Integrations
ABAP
Yes
Fortran
Yes
Java
Yes
Model Context Protocol (MCP)
No
Rust
Yes
Tinker
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
Pricing Details
$20 per month
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
No
On-Premises
No
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
Cosine
Country
United Kingdom
Website
cosine.sh/blog/lumen-outpost-benchmark-report