TL;DR: Google has launched Gemini 3, a new foundation model built from the ground up with multimodal capabilities supporting text, images, audio, video, and full-length YouTube videos.
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📺 Title: Gemini 3 is the best model on earth
⏱️ Duration: 716
👤 Channel: Matthew Berman
🎯 Topic: Gemini Best Model
💡 This comprehensive article is based on the tutorial above. Watch the video for visual demonstrations and detailed explanations.
Google has officially launched Gemini 3—and it’s not just an incremental upgrade. It’s a revolutionary leap forward in artificial intelligence, redefining what’s possible across reasoning, multimodal understanding, and real-world task automation. In this comprehensive guide, we’ll unpack every detail from the official launch, including benchmark results, real-world applications, new tools like Gemini Agent and Anti-Gravity, and how you can start using Gemini 3 today—especially in enterprise environments via Box.com.
Based strictly on the full video transcript, this article extracts every insight, number, example, and technique shared—no detail overlooked. Whether you’re a developer, enterprise user, content creator, or AI enthusiast, this is your definitive resource on why Gemini 3 is now the Gemini best model and how to leverage it.
What Is Gemini 3? A Brand-New Foundation Model
Gemini 3 isn’t a fine-tuned version of an older model—it’s a completely new foundation model built from the ground up. According to Google’s model card, it supports multiple input modalities: text, images, audio, video files, and even full-length YouTube videos.
Key technical specs include:
- Input context window: Up to 1 million tokens
- Output tokens: Up to 64,000
- Architecture: Sparse Mixture of Experts (MoE)
- Hardware: Trained and run on Google’s custom TPU architecture—a major competitive moat
This hardware-software integration gives Google a significant edge in both training efficiency and inference speed, making Gemini 3 not just smarter, but faster and more scalable in production.
Three Flavors of Gemini 3: Pro, Deep Think, and Standard
Google launched three distinct versions of Gemini 3 to serve different use cases:
- Gemini 3 (standard)
- Gemini 3 Pro Preview
- Gemini 3 Deep Think
Each variant is optimized for specific performance profiles, with Deep Think allocating more computational resources to the “thinking” phase for complex reasoning tasks.
Benchmark Domination: How Gemini 3 Crushes the Competition
Gemini 3 doesn’t just compete—it dominates. Across multiple high-stakes AI benchmarks, it consistently outperforms rivals like GPT-5.1, Claude Sonnet 4.5, and Cloud Sonnet 4.5.
Humanity’s Last Exam: Reasoning Under Pressure
This benchmark tests general reasoning and knowledge without external tools. Results:
| Model | Score (No Tools) | Score (With Code + Search) |
|---|---|---|
| Gemini 3 | 37.5% | 45.8% |
| Gemini 2.5 Pro | 21% | — |
| Cloud Sonnet 4.5 | 13% | — |
| GPT-5.1 | 26.5% | — |
| Amy 2025 | — | 100% (with code execution) |
Note: Amy 2025 achieved a perfect score only with code execution enabled, while Gemini 3 leads among widely available models.
Gemini 3 Deep Think: The Reasoning Powerhouse
When extra “thinking time” is allowed, Gemini 3 Deep Think pushes performance even higher:
- Humanity’s Last Exam: 41% (vs. 37.5% for Gemini 3 Pro)
- GPQA (Scientific Knowledge): 93.8% — #1 globally
For context, GPQA is a notoriously difficult benchmark requiring deep scientific understanding. Gemini 3 Pro took second place, with GPT-5 models trailing in third and fourth.
Arc AGI 2: The True Test of General Intelligence
Arc AGI 2 presents visual reasoning puzzles where the AI must infer transformation rules from input-output examples—a key indicator of generalized intelligence.
Here’s how models performed:
| Model | Arc AGI 2 Score |
|---|---|
| Gemini 3 Deep Think | 45.1% |
| GPT-5.1 | 17% |
| GPT-5 Pro | 15% |
| Claude Sonnet 4.5 | 13.6% |
| Gemini 2.5 Pro | ~4.5% (10x worse) |
This represents a 10x improvement
Vending Bench: Long-Horizon Planning in Real Economic Environments
Vending Bench simulates running a real vending machine business over time. The AI must:
- Stock appropriate products
- Adjust inventory based on customer demand
- Refill at optimal times
- Maximize net worth over a full year
This tests long-horizon coherence and economic reasoning—critical for future AI agents managing real businesses.
Vending Bench Results
| Model | Final Net Worth |
|---|---|
| Gemini 3 | $5,478.16 |
| Claude Sonnet 4.5 | $3,800 |
| GPT-5.1 | Significantly lower |
| Gemini 2.5 Pro | Plateaued early, then lost money |
Crucially, Gemini 3’s net worth kept rising after one year, while competitors plateaued or declined—demonstrating unmatched strategic persistence.
Box.com Enterprise Benchmark: Real-World Document Intelligence
Box.com, the enterprise content management platform and video sponsor, ran a custom benchmark focused on multi-step reasoning over unstructured documents—mirroring real office workflows.
The task: extract insights from multiple documents and solve complex, multi-step logic problems.
Performance Jump: Gemini 2.5 Pro vs. Gemini 3 Pro
| Sector | Gemini 2.5 Pro | Gemini 3 Pro | Improvement |
|---|---|---|---|
| Overall | 63% | 85% | +22 points |
| Healthcare & Life Sciences | 45% | 94% | +49 points |
| Media & Entertainment | 47% | 92% | +45 points |
| Financial Services | 51% | 60% | +9 points |
This massive leap shows Gemini 3’s strength in enterprise automation—especially in regulated, document-heavy industries.
How to Use Gemini 3 with Box Today
Box users can access Gemini 3 immediately via:
- Box AI Studio: No-code interface for document analysis
- Box API: For developers building custom AI workflows
Given the 22-point average performance gain, upgrading to Gemini 3 in Box could dramatically accelerate contract review, compliance checks, and data extraction tasks.
Unmatched Video Understanding: Frame-by-Frame Analysis
Gemini 3 supports text, images, audio, code, and video—but its video understanding is truly unique.
Unlike other models that rely only on transcripts, Gemini 3 analyzes videos frame by frame. It can process full YouTube videos (thanks to Google’s ownership of both platforms) and answer precise visual questions.
Real Example: Analyzing a YouTube Video
The speaker pasted a link to their latest YouTube video into Gemini 3. Within seconds, it loaded the 111,000-token video and answered:
“The frame at 3 minutes features a split screen layout. On the right side, the presenter, a man with short curly hair wearing a light blue button-down shirt, is speaking into a microphone. On the left side, there’s a graphic displaying a snippet of text from a report—likely the Anthropic paper being discussed. The text is clearly legible and reads…”
This level of visual detail—identifying clothing, layout, and on-screen text—demonstrates true multimodal comprehension. The speaker uses this feature regularly to generate accurate chapter markers for YouTube videos.
How to Use This Feature
- Go to Google AI Studio (or Gemini app)
- Paste a YouTube URL
- Ask questions about specific timestamps
No downloading or uploading required—Google’s ecosystem integration makes it seamless.
Google Search Gets a Gemini 3 Overhaul
On day one of the launch, Gemini 3 was integrated into Google Search’s AI Mode. But this isn’t just a chatbot sidebar—it’s a complete reimagining of search results.
Dynamic UI Generation
When you enable AI Mode and upload a document (e.g., a research paper), Gemini 3:
- Reads and understands the full document
- Generates a custom, dynamic user interface tailored to your query
- Presents answers in a structured, interactive format—not just text
As the speaker notes: “This part of Google search did not exist. And now it does.” This signals a future where every Google search result page could be dynamically generated based on user intent and context.
Gemini Agent: Your AI Task Executor
The updated Gemini app now includes Gemini Agent—a lab feature that doesn’t just answer questions but completes real tasks on your behalf.
Example: Organize Your Gmail Inbox
Here’s how it works step-by-step:
- Open Gemini app → Tools → Agent (lab feature)
- Select “Organize my inbox”
- Gemini retrieves all unread emails
- It builds a dynamic review UI with bulk-action suggestions
- You can accept all, reject all, or review individually
- It even drafts contextual email responses based on conversation history
This moves beyond passive assistance to active task completion—a major step toward autonomous AI agents.
Introducing Anti-Gravity: Google’s VS Code Fork for AI Coding
Google also launched Anti-Gravity—its own AI-native coding environment built as a VS Code fork. It directly competes with Cursor, Windsurf, Replit, and Factory.
Key features:
- Supports Gemini models (including Gemini 3 Pro High)
- Also compatible with open-source models like GPT-OSS (OpenAI) and Anthropic’s Sonnet family
- Designed for “vibe coding”—intuitive, conversational development
While a full review is pending (“Video coming soon,” says the speaker), Anti-Gravity positions Google as a serious player in the AI coding space.
SWEBench Verified: The One Benchmark Gemini Didn’t Win
Gemini 3 came close—but didn’t win—on SWEBench Verified, which tests code repository understanding and bug fixing.
| Model | SWEBench Verified Score |
|---|---|
| Claude Sonnet 4.5 | 77.2% |
| Gemini 3 Pro | 76.2% |
Despite losing by just 1%, Gemini 3’s near-perfect score confirms its elite coding capabilities—especially when combined with tools like Anti-Gravity.
Why Google’s TPU Architecture Is a Game-Changer
A recurring theme in the transcript is Google’s custom TPU chips. Unlike competitors relying on NVIDIA GPUs, Google uses its own hardware for both pre-training and inference.
This creates a powerful “moat” because:
- TPUs are optimized specifically for Google’s AI workloads
- Lower latency and higher throughput during inference
- Better cost efficiency at scale
- Tighter integration between model design and hardware
For enterprise users, this translates to faster, more reliable AI services—especially for high-volume applications like search or document processing.
Real-World Use Case: YouTube Chapter Markers
The speaker shares a practical, daily use of Gemini 3’s video understanding:
“I use this all the time for helping me create chapter markers for my YouTube videos.”
By analyzing frame content, Gemini 3 can auto-generate timestamps for key segments—saving hours of manual review. This is just one example of how multimodal AI can enhance content creation workflows.
Enterprise Recommendation: Start with Box AI Studio
Given the dramatic benchmark improvements in document reasoning, the speaker strongly recommends:
“We use Box at my company. I suggest you use it at yours. Give it a try. They’ve been a fantastic partner.”
For businesses already using Box, activating Gemini 3 via AI Studio is the fastest path to ROI—especially in healthcare, media, and finance, where performance jumped by 45–49 points.
What’s Next? Testing and Adoption Roadmap
The speaker plans to:
- Deeply test Gemini Agent starting “this week”
- Release a follow-up video with hands-on results
- Explore Anti-Gravity for coding tasks
For readers, the immediate action items are:
- Try Gemini 3 in Google AI Studio with a YouTube link
- If using Box, enable Box AI Studio with Gemini 3
- Experiment with AI Mode in Google Search
- Watch for the upcoming Gemini Agent deep dive
Conclusion: Why Gemini 3 Is the New Best Model
Gemini 3 isn’t just another AI release—it’s a system-wide transformation of Google’s ecosystem. From frame-level video understanding to long-horizon economic planning, from dynamic search UIs to autonomous task execution, it sets a new standard across every dimension of AI performance.
Key takeaways:
- ✅ #1 or #2 on nearly every major benchmark
- ✅ True multimodal understanding—especially video
- ✅ Enterprise-ready via Box integration
- ✅ Hardware advantage with custom TPUs
- ✅ Active task completion via Gemini Agent
If you’re evaluating the Gemini best model for personal, creative, or enterprise use—Gemini 3 is the definitive choice in 2024. Start experimenting today, and stay tuned for advanced use cases as Google rolls out more features.
