Gemini 4 Carbon
Gemini 4 Carbon is Google DeepMind's frontier model for long-horizon engineering, coding, agentic workflows, and cybersecurity defense. Google says its initial rollout is limited to selected cyber defenders and trusted partners, with broader developer access planned.
1,000k
~750k words input
$2 / $10
Prompt / Completion per 1M
88.2 %
SEC-bench Pro
Cloud Managed
Zero local VRAM
Holistic Capability Distribution
Normalized 0-100 rating vectors balanced across intelligence, throughput, and economics.
Verified LLM Benchmarks
Empirical evaluations across academic reasoning, software engineering, agentic execution, and human preference.
Architectural Strengths vs. Operational Considerations
An objective technical balance sheet analyzing deployment advantages and production constraints.
Key Architectural Strengths
- Long-horizon engineering workflows
- Cybersecurity vulnerability detection and patching
- Secure code generation
- Agentic coding tasks
Operational Considerations
- Public access is still staged
- Benchmark results are primarily vendor-reported
- The introductory price may increase after rollout
Hardware & Execution Parameters
Architecture Engineering & Capability Deep-Dive
Evaluation Profile & Reasoning Capabilities
Designed for sustained, multi-step engineering tasks that can continue through dead ends and revise work across large codebases.
Inference Economics & Cost Optimization
Google announced an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input at a 95% discount.
Primary Production Workloads & Suitability
Cloud Deployment Architecture & Hardware Sizing
Cloud Deployment Architecture
Distributed enterprise serving infrastructure, autoscaling semantics, and runtime execution profile.
Proprietary commercial model hosted on managed multi-region clusters with automatic autoscaling, high availability, and prompt prefix caching.
Google-managed cloud service
Continuous autoscaling with regional failover
0 GB Local VRAM
Inference executed on hyperscaler accelerator clusters
1,000k tokens
Supported with automated KV cache prefix compression
SDK Installation
Official Repositories & Papers
Compare Showdowns
Gemini 4 Carbon vs Gemini 2.0 Flash
Compare Gemini 4 Carbon against Gemini 2.0 Flash's verified benchmarks, context window, and pricing.
Gemini 4 Carbon vs Claude Sonnet 4
Compare Gemini 4 Carbon against Claude Sonnet 4's verified benchmarks, context window, and pricing.
Gemini 4 Carbon vs Claude Sonnet 4.5
Compare Gemini 4 Carbon against Claude Sonnet 4.5's verified benchmarks, context window, and pricing.
Gemini 4 Carbon vs Claude Sonnet 4.6
Compare Gemini 4 Carbon against Claude Sonnet 4.6's verified benchmarks, context window, and pricing.
Commercial Token Rates & Cost Estimator
$2.00 / 1M
Standard prompt context ingestion
$10.00 / 1M
Generated completion & thinking tokens
$0.10 / 1M
Re-used prompt prefix context
Monthly Production Cost Simulator
$486.00
Includes prompt caching
-$114.00
Saved via prefix context caching
Comparable Foundation Architectures
Alternative foundation models with comparable intelligence benchmarks, context windows, and deployment profiles.
Gemini 2.0 Flash
Google's next-generation multimodal model built for the agentic era with sub-second latency, native tool use, and a 1,000,000 token context window.
Claude Sonnet 4
Claude Sonnet 4 is Anthropic's premier balanced engineering model for the Claude 4 generation, engineered for rapid autonomous coding agents, multi-step tool execution, and cost-effective enterprise workflows.
Claude Sonnet 4.5
Claude Sonnet 4.5 establishes a new frontier standard in autonomous software engineering with 80%+ SWE-bench Verified resolution, expanded 250k context, and optimized test-time execution.
Claude Sonnet 4.6
Claude Sonnet 4.6 delivers 300k context window, 83.2% SWE-bench Verified score, and reduced $2.50/$12.50 token economics for large-scale enterprise software agent automation.
SDK Installation & API Integration
// No TypeScript snippet availableFrequently Asked Questions about Gemini 4 Carbon
Engineering specifications, VRAM sizing, commercial licensing terms, token economics, and empirical benchmark evaluations.
Google announced a staged rollout beginning with selected cyber defenders and trusted partners. Broader access for developers, businesses, and consumers is planned but not yet generally available.
It is designed for long-horizon engineering, coding, agentic workflows, and cybersecurity defense, including vulnerability discovery and remediation.