Average Ratings 1 Rating
Average Ratings 1 Rating
Description
Gemini 3.6 Flash is Google’s workhorse Flash model for developers and enterprises building production AI agents at scale. The model is designed to deliver higher quality than Gemini 3.5 Flash while improving token efficiency, latency, and overall task cost. Google says Gemini 3.6 Flash uses 17% fewer output tokens than 3.5 Flash on the Artificial Analysis Index and can show even larger efficiency gains on certain software engineering benchmarks. It is priced lower than 3.5 Flash at $1.50 per 1 million input tokens and $7.50 per 1 million output tokens. Gemini 3.6 Flash improves performance in coding, ML research, computer use, knowledge work, document parsing, chart analysis, report drafting, and data-heavy workflows. The model also supports built-in computer use through the Gemini API and Gemini Enterprise, making it more useful for agentic systems that need to operate across digital environments. Google highlights customer use cases involving financial transcript analysis, code migrations, visual workflows, and interactive design tools. The model includes enhanced Frontier Safety safeguards for CBRN and cyber offense misuse while aiming to reduce unnecessary refusals for beneficial uses. By combining efficiency, stronger reasoning, multimodal ability, computer use, and enterprise availability, Gemini 3.6 Flash gives teams a practical model for scaling AI agents in production.
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
API Access
Has API
Integrations
.NET
Android Studio
Bash
C#
CSS
Dart
Gemini 3.5 Flash
Gemini 3.5 Flash-Lite
Google AI Mode
Google AI Overviews
Integrations
.NET
Android Studio
Bash
C#
CSS
Dart
Gemini 3.5 Flash
Gemini 3.5 Flash-Lite
Google AI Mode
Google AI Overviews
Pricing Details
$1.50 per 1M tokens (input)
$1.50/1M input tokens and $7.50/1M output tokens
Free Trial
Free Version
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
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
Founded
1998
Country
United States
Website
gemini.google.com
Vendor Details
Company Name
Thinking Machines Lab
Founded
2025
Country
United States
Website
thinkingmachines.ai/news/inkling-small/