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Average Ratings 0 Ratings
Description
Gemini 4 Carbon is an experimental AI model reportedly being developed by Google DeepMind for advanced reasoning and software engineering applications. The model has appeared in reports describing internal testing of multiple Gemini 4 variants, including Argon, Barium, and Carbon. Carbon has reportedly been integrated into Google's internal Jetski coding environment for evaluation by company employees. Early internal feedback has highlighted its potential performance in complex coding tasks, although independently verified benchmark results have not been published. Its reported development suggests an emphasis on improving AI-assisted programming and technical problem-solving capabilities. Potential use cases include code generation, debugging, codebase analysis, software maintenance, and autonomous development workflows. Carbon belongs to the broader Gemini 4 research effort, which includes publicly released models supporting multimodal reasoning, software engineering, and AI agent applications. However, Google has not confirmed whether Carbon will become a standalone product, an update to Gemini 4 Argon, or a different publicly branded model. Technical specifications, API availability, pricing, deployment options, and release timing remain unannounced.
Description
Qwen3.5 represents a major advancement in open-weight multimodal AI models, engineered to function as a native vision-language agent system. Its flagship model, Qwen3.5-397B-A17B, leverages a hybrid architecture that fuses Gated DeltaNet linear attention with a high-sparsity mixture-of-experts framework, allowing only 17 billion parameters to activate during inference for improved speed and cost efficiency. Despite its sparse activation, the full 397-billion-parameter model achieves competitive performance across reasoning, coding, multilingual benchmarks, and complex agent evaluations. The hosted Qwen3.5-Plus version supports a one-million-token context window and includes built-in tool use for search, code interpretation, and adaptive reasoning. The model significantly expands multilingual coverage to 201 languages and dialects while improving encoding efficiency with a larger vocabulary. Native multimodal training enables strong performance in image understanding, video processing, document analysis, and spatial reasoning tasks. Its infrastructure includes FP8 precision pipelines and heterogeneous parallelism to boost throughput and reduce memory consumption. Reinforcement learning at scale enhances multi-step planning and general agent behavior across text and multimodal environments. Overall, Qwen3.5 positions itself as a high-efficiency foundation for autonomous digital agents capable of reasoning, searching, coding, and interacting with complex environments.
API Access
Has API
Yes
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
OpenClaw
Yes
BaseRT
No
C#
Yes
CSS
Yes
Claw Code
No
Dart
Yes
Gemini 3.8 Live
Yes
Gemini Spark
Yes
Go
Yes
Google
Yes
Integrations
OpenClaw
Yes
BaseRT
Yes
C#
No
CSS
No
Claw Code
Yes
Dart
No
Gemini 3.8 Live
No
Gemini Spark
No
Go
No
Google
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
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
Yes
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
No
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
Founded
1998
Country
United States
Website
gemini.com
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
qwen.ai
Product Features
Product Features
Alternatives
No Alternatives