# The Full Stack (fullstackdeeplearning.com) vs Gemini 4 Carbon (Gemini Carbon 4)

The Full Stack (fullstackdeeplearning.com) records 46,082 monthly visits with +6.6% month-over-month growth and Free (educational content) pricing. Gemini 4 Carbon (Gemini Carbon 4) records 4,339,429 monthly visits with +12.7% growth and Freemium pricing.

| Metric | [The Full Stack (fullstackdeeplearning.com)](https://openaitools.app/tool/fullstackdeeplearning-com) | [Gemini 4 Carbon (Gemini Carbon 4)](https://openaitools.app/tool/gemini-4-carbon) |
| :--- | :--- | :--- |
| Website URL | https://fullstackdeeplearning.com | https://deepmind.google/models/gemini/ |
| Categories | AI Course, Large Language Models (LLMs), Prompt Engineering, AI Developer Tools | Large Language Models (LLMs), AI Models, AI Code Assistant, AI Agent |
| Pricing Model | Free (educational content) | Freemium |
| Monthly Visits | 46,082 | 4,339,429 |
| MoM Growth Rate | +6.6% | +12.7% |
| Primary Market | United States | United States |
| Direct Visits | 26,064 | 899,124 |
| Review Score | 4.6 | 4.8 |
| Saved Count | 1 | 1,420 |
| Supported Platforms | Website | Website, API |

## The Full Stack (fullstackdeeplearning.com)

Full Stack Deep Learning began as a course teaching engineers to take deep learning from notebook to production, and it has grown into a broader educational hub. The site hosts complete course materials — lecture pages, slides, lab notebooks, and video walkthroughs — for both its Deep Learning Course and its LLM Bootcamp, so learners can follow along at their own pace without paying for a seat.

The curriculum is deliberately full-stack rather than model-centric. The Deep Learning Course covers development infrastructure, experiment management, troubleshooting and testing, data management and annotation, deployment, continual learning, and model monitoring, plus team and project management and ethics. The LLM Bootcamp goes into prompt engineering, augmented language models, LLMOps, and user experience for language interfaces, and includes build-along project walkthroughs.

Beyond courses, the site publishes a blog, hosts a manifesto on building AI products collaboratively, and maintains reference material such as a cloud GPU pricing guide. Because the materials are released publicly and remain accessible, the site functions as a long-lived library rather than a time-boxed bootcamp, and its audience spans individual developers, teams, and educators looking for structured material.

**Pricing & Plans:** The published course material on fullstackdeeplearning.com is available free of charge. There is no conventional subscription or per-seat pricing listed on the site; the project has historically been supported by sponsors and community interest. Any future paid programs would be announced on the site.

- **Free LLM Bootcamp materials:** Lecture pages and resources covering prompt engineering, augmented language models, LLMOps, and language UI/UX.
- **Full Deep Learning Course archive:** Multi-year course content on infrastructure, data management, deployment, monitoring, and ML team organization.
- **Working with AI Agents:** Current material on collaborating with and building agent-based systems, including a perspective on multiplayer AI.
- **Cloud GPU reference:** A maintained guide to cloud GPU options that helps teams choose compute for training and inference.
- **Blog and community resources:** Articles and updates aimed at practitioners building AI products, with a newsletter to follow new releases.

**Strengths:** Course materials are open and free to follow at your own pace; Covers the full product lifecycle, not just model training; Maintained across multiple years, so it documents how practice evolved; Includes hands-on labs and build-along project walkthroughs

**Limitations:** Some flagship courses date from 2021-2023, so tooling specifics age; Not an interactive cohort programme, so there is no instructor feedback; Sparse on formal certification or structured assessments

[Profile (Markdown)](https://openaitools.app/tool/fullstackdeeplearning-com.md)

## Gemini 4 Carbon (Gemini Carbon 4)

Gemini 4 Carbon (frequently searched as Gemini Carbon 4) is Google DeepMind's flagship frontier model announced on October 28, 2026, arriving just two weeks after Gemini 4 Argon. Built for sustained, multi-day agentic engineering and autonomous cyberdefense, Gemini 4 Carbon debuted at #1 on the Artificial Analysis Intelligence Index v5.0 with a score of 59—outperforming Claude Opus 5.5 (58), GPT-6 Astra (57), and Gemini 4 Argon (50) while using 29% fewer output tokens per task than Claude Opus 5.5.

Across the cybersecurity defense lifecycle, Gemini 4 Carbon establishes a decisive frontier lead: it scores 88.2% on SEC-bench Pro for discovering real-world software vulnerabilities, 54.8% on ExploitGym for validating exploitability, and 71.0% on Collinear's CWE-bench for generating root-cause patches. Internal Google evaluations show more than a 2x uplift in generating vulnerability-free code over Gemini 4 Argon, and the Chrome security team reported 10x higher patch quality compared to competing frontier models. Beyond security, Carbon jumps +89 Elo to #4 (1768) on WebDev Arena, reaches 96.2% F1 on GraphWalks (256K–1M long-context reasoning), scores 80.0% on RiemannBench, and ranks #1 of 93 models on Vals AI's Legal Research Bench.

Google is rolling out Gemini 4 Carbon through a deliberate staged release: initial access began via Google's Fairwind Program for vetted cybersecurity defenders and U.S. government pre-release testing partners, followed by broader availability across Google AI Ultra and Pro subscriptions, Google AI Studio, Vertex AI, and the agent-first Google Antigravity IDE. API pricing launches with a 50% introductory discount at $2.00 per 1M input tokens and $10.00 per 1M output tokens ($4.00 / $20.00 standard pricing after the promotional period), with cached input tokens discounted by 95% ($0.10–$0.20 per 1M).

**Pricing & Plans:** API introductory launch pricing (50% off): $2.00 / 1M input tokens and $10.00 / 1M output tokens ($4.00 / $20.00 standard rate), plus 95% off cached input tokens ($0.10–$0.20 / 1M). Staged access via Google's Fairwind Program, Google AI Studio, Vertex AI, and Google AI Ultra ($99.99–$199.99/mo) & Pro ($19.99/mo).

- **#1 on Artificial Analysis Intelligence Index v5.0 (Score 59):** Leads overall frontier intelligence across HLE-Diamond, Terminal-Bench-Science (64.8%), AA-Omniscience, and AutomationBench-AA, scoring 9 points higher than Gemini 4 Argon at comparable per-task cost ($7.76).
- **Full-Lifecycle Cybersecurity Defense (SEC-bench Pro 88.2%):** State-of-the-art autonomous vulnerability discovery (88.2% SEC-bench Pro), exploit validation (54.8% ExploitGym), and root-cause patching (71.0% CWE-bench), generating 2x more secure code than Argon.
- **Multi-Day Long-Horizon Agentic Engineering:** Persists for days through dead ends and complex tool-call loops across large codebases and low-level systems, scoring 65.2% on Terminal-Bench 4.0 and 1768 Elo (#4, +89 Elo) on WebDev Arena.
- **1M-Token Native Multimodal Context (96.2% GraphWalks F1):** Processes text, code, images, audio, speech, and video within a 1-million-token context window, achieving 96.2% F1 on 256K–1M GraphWalks and 72.5% on Chartography.
- **Hardened Alignment & Prompt-Injection Resilience:** Combines chain-of-thought monitoring, real-time misuse defenses, and high-pressure alignment training that cuts unsupported claims and fabrications by 2x compared to Gemini 4 Argon.

**Strengths:** Ranked #1 overall on Artificial Analysis Intelligence Index v5.0 (59), ahead of Claude Opus 5.5 (58) and GPT-6 Astra (57); Unmatched cybersecurity benchmark leadership on SEC-bench Pro (88.2%), ExploitGym (54.8%), and CWE-bench (71.0%); Aggressive 50% launch API discount ($2 / $10 per 1M tokens) with 95% off context caching and 29% lower output token consumption than Claude Opus 5.5; True 1M-token multimodal context window with a 12-point jump on 256K–1M GraphWalks (96.2% F1 vs Argon's 84.2%)

**Limitations:** Staged rollout starts with Google's Fairwind Program for cyber defenders before general availability in Google AI Studio and Gemini apps; Standard API pricing doubles to $4.00 / $20.00 per 1M tokens once the introductory 50% launch discount period ends; High reasoning effort modes exhibit longer time-to-first-answer-token latency (9.75s–23.45s) on deep multi-step tasks

[Profile (Markdown)](https://openaitools.app/tool/gemini-4-carbon.md)

## Frequently Asked Questions

### How do The Full Stack (fullstackdeeplearning.com) and Gemini 4 Carbon (Gemini Carbon 4) compare in monthly traffic?

The Full Stack (fullstackdeeplearning.com) has 46,082 monthly visits, while Gemini 4 Carbon (Gemini Carbon 4) has 4,339,429. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

The Full Stack (fullstackdeeplearning.com) has a month-over-month growth rate of +6.6%; Gemini 4 Carbon (Gemini Carbon 4) has +12.7%.

### How does pricing compare?

The Full Stack (fullstackdeeplearning.com): Free (educational content). The published course material on fullstackdeeplearning.com is available free of charge. There is no conventional subscription or per-seat pricing listed on the site; the project has historically been supported by sponsors and community interest. Any future paid programs would be announced on the site. Gemini 4 Carbon (Gemini Carbon 4): Freemium. API introductory launch pricing (50% off): $2.00 / 1M input tokens and $10.00 / 1M output tokens ($4.00 / $20.00 standard rate), plus 95% off cached input tokens ($0.10–$0.20 / 1M). Staged access via Google's Fairwind Program, Google AI Studio, Vertex AI, and Google AI Ultra ($99.99–$199.99/mo) & Pro ($19.99/mo).

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | Highly efficient reasoning models with exceptionally low API pricing, but offers less specialized multimodal agentic tooling. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [OpenAI Platform](https://openaitools.app/tool/openai) | 234,678,639 | -9.6% | Paid | Industry-standard proprietary frontier models with powerful developer APIs, but lacks Google's native massive context window. | [.md](https://openaitools.app/tool/openai.md) |
| 3 | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | 35,101,353 | -6.2% | Freemium | Powerful open-weight multimodal models with strong multilingual support, but requires self-hosting or third-party inference. | [.md](https://openaitools.app/tool/qwen-4.md) |
| 4 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Unified API gateway offering access to hundreds of models, but lacks a single native frontier model. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 5 | [BigModel](https://openaitools.app/tool/bigmodel) | 5,700,686 | -17% | Freemium | Zhipu AI's robust GLM language and multimodal APIs, but with less global developer ecosystem support. | [.md](https://openaitools.app/tool/bigmodel.md) |
| 6 | [Gemma Open Models by Google](https://openaitools.app/tool/gemma-open-models-by-google) | 4,900,914 | -13.5% | Freemium, Paid | Lightweight open-weights models from Google for local deployment, but less capable than frontier closed models. | [.md](https://openaitools.app/tool/gemma-open-models-by-google.md) |
| 7 | [DeepLearning.AI](https://openaitools.app/tool/deeplearning-ai) | 2,562,512 | -7.2% | Freemium | AI engineering courses, certificates, and the world's biggest AI newsletter | [.md](https://openaitools.app/tool/deeplearning-ai.md) |
| 8 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Serverless inference for open-source models with high-performance GPU clusters, but requires managing your own model weights. | [.md](https://openaitools.app/tool/together-ai.md) |
| 9 | [Tencent Hunyuan](https://openaitools.app/tool/tencent-hunyuan-large-model) | 1,485,463 | -1.2% | Contact for Pricing | Comprehensive multimodal foundation model family from Tencent, but primarily targeted at Asian enterprise markets. | [.md](https://openaitools.app/tool/tencent-hunyuan-large-model.md) |
| 10 | [The Rundown AI](https://openaitools.app/tool/the-rundown-ai) | 1,018,070 | +28.6% | Free | The top AI news and how to apply it, in five minutes a day | [.md](https://openaitools.app/tool/the-rundown-ai.md) |

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Source: https://openaitools.app/compare/fullstackdeeplearning-com-vs-gemini-4-carbon

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