Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Gemini Enterprise Agent Platform Reviews & Ratings
    1,161 Ratings
    Company Website
  • LTX Reviews & Ratings
    182 Ratings
    Company Website
  • Evertune Reviews & Ratings
    1 Rating
    Company Website
  • Gemini Credit Card Reviews & Ratings
    2 Ratings
    Company Website
  • Gushwork Reviews & Ratings
    29 Ratings
    Company Website
  • AthenaHQ Reviews & Ratings
    50 Ratings
    Company Website
  • Google Workspace Reviews & Ratings
    69,271 Ratings
    Company Website
  • HubSpot AEO Reviews & Ratings
    151 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    2,027 Ratings
    Company Website
  • LM-Kit.NET Reviews & Ratings
    29 Ratings
    Company Website

What is Gemini 4 Carbon?

Gemini 4 Carbon is an advanced multimodal artificial intelligence model developed by Google DeepMind for cybersecurity research, software engineering, long-horizon autonomous agents, and complex analytical workflows. The model builds on Gemini 4 Argon with improvements in reasoning, coding, scientific tasks, multimodal understanding, and sustained execution of multistep engineering projects. Its cybersecurity capabilities cover the vulnerability management lifecycle, including identifying software weaknesses, verifying exploitability, and generating patches that address underlying security flaws. In Google's published evaluations, Gemini 4 Carbon achieved 88.2% on SEC-bench Pro for vulnerability discovery, 54.8% on ExploitGym for exploit validation, and 71.0% on CWE-bench for vulnerability remediation. Internal evaluations also showed more than twice the secure code generation success rate of Gemini 4 Argon. The model supports long-running agentic workflows that can investigate difficult bugs, analyze large software repositories, and perform iterative problem-solving across extended execution periods. Its software development capabilities include code generation, debugging, low-level systems analysis, full-stack web development, and automated implementation of complex engineering tasks. Gemini 4 Carbon incorporates a multilayered safety architecture with misuse prevention, prompt injection defenses, behavioral monitoring, and controls intended to reduce unauthorized actions. Google reports improvements in factual reliability, task completion, and instruction alignment, including approximately half as many unsupported claims compared with Gemini 4 Argon in internal evaluations.

What is DeepSWE?

DeepSWE represents a groundbreaking advancement in open-source coding agents, harnessing the Qwen3-32B foundation model trained exclusively through reinforcement learning (RL) without the aid of supervised fine-tuning or proprietary model distillation. Developed using rLLM, which is Agentica's open-source RL framework tailored for language-driven agents, DeepSWE functions effectively within a simulated development environment provided by the R2E-Gym framework. This setup equips it with a range of tools, such as a file editor, search functions, shell execution, and submission capabilities, allowing the agent to adeptly navigate extensive codebases, modify multiple files, compile code, execute tests, and iteratively generate patches or fulfill intricate engineering tasks. In addition to mere code generation, DeepSWE exhibits sophisticated emergent behaviors; when confronted with bugs or feature requests, it engages in critical reasoning regarding edge cases, searches for existing tests in the codebase, proposes patches, creates additional tests to avert regressions, and adapts its cognitive strategies based on the specific challenges presented. This remarkable adaptability and efficiency position DeepSWE as a formidable asset in the software development landscape, empowering developers to tackle complex projects with greater ease and confidence. Its ability to learn from each interaction further enhances its performance, ensuring continuous improvement over time.

Media

Media

Integrations Supported

Bind AI
Cursor
Dart
Gemini 3.5 Flash
Gemini 3.5 Flash Cyber
Gemini Spark
Go
Google AI Mode
Google Antigravity
HTML
Java
JavaScript
Kotlin
Model Context Protocol (MCP)
OfoxAI
Python
Replit
Wikis.ai
XML

Integrations Supported

Together AI

API Availability

Has API

API Availability

Pricing Information

$2 per 1M tokens (input)
$2 per million input tokens and $10 per million output tokens, with cached input tokens priced at 95% off input token price.

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

gemini.com

Company Facts

Organization Name

Agentica Project

Date Founded

2025

Company Location

United States

Company Website

agentica-project.com

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Vision Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Popular Alternatives

Popular Alternatives

Devstral 2 Reviews & Ratings

Devstral 2

Mistral AI
GPT-6.1 Sol Reviews & Ratings

GPT-6.1 Sol

OpenAI
Devstral Small 2 Reviews & Ratings

Devstral Small 2

Mistral AI
DeepCoder Reviews & Ratings

DeepCoder

Agentica Project
KAT-Coder-Pro V2 Reviews & Ratings

KAT-Coder-Pro V2

StreamLake