# Gemini 3: Expansion, Opportunity, and Industry Reactions
Gemini 3’s release is **more than a parameter update** — it represents a **forceful expansion of model boundaries**.
Like a massive, multifaceted polyhedron, it simultaneously spans **Vibe**, **Coding**, **General-purpose Agents**, **Front-end Design**, and **Game Engines** — touching some of the hottest current AI tracks.
This “capability overflow” raises a challenging question for entrepreneurs:
**Will this open new possibilities, or will vertical applications dissolve into the model’s borderless expansion?**
We interviewed **seven AI companies across different sectors** to explore their reactions.
**Findings:**
- Some founders were **so excited they couldn’t sleep** — experiencing a “Ghibli moment” during late-night tests.
- Others stayed **calm and skeptical** — insisting that **data barriers** and **real-time capability** remain stronger moats than general-purpose model hype.
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## Flowith — Gemini 3 Aligns Perfectly with Agent Needs
> **About:** Interactive canvas content creation Agent platform. Launched **Flowith OS**, an operating system natively designed for Agents, in October.
**Q (Silicon Planet):** Does such a powerful model reduce the value of general-purpose Agents?
**Derek, Flowith Founder:**
- **Key Improvements:** Stronger **visual understanding**, **code generation**, **long-task handling**.
- These are *must-have* for Agent-based businesses — especially consumer-facing AI.
- **Gemini’s speed & cost-effectiveness** remain standout advantages.
- Integrating Gemini 3 into Flowith Neo Agent and Flowith OS is already underway.
- Pattern seen with platforms like **Cursor** and **Perplexity**: mainstream adoption follows model upgrades.
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## DoudouAI — Matching Models to the Right Scenarios is Key
> **About:** AI gaming partner providing in-game voice strategy guidance and companionship during live team play.
**Q:** Why the excitement about Gemini 3’s gaming potential?
**Wang Bihao, Co-founder:**
- Benchmark leap: **Screen Sport Pro jumped from 17.4 → 72** — now truly understands screens in real time.
- Video test: Quality on par with human commentators (tone still flatter).
- **Latency challenge:** Large-parameter reasoning models require 10–20 s processing; unsuitable for live play.
- **Best Fit:** Post-match analysis — like meeting summaries turned into to-dos.
**Overseas Focus:**
Promoting post-match AI analysis for titles like *League of Legends* in global markets.
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### Domain Expertise vs. General Models
**Three differentiators for DoudouAI:**
1. **Gaming-specialized training** — deeper recognition than general-purpose models.
2. **Response speed trade-offs** — faster than Gemini 3 in live gaming scenarios.
3. **Emotional value layer** — using character personas to deliver feedback.
**Competitive Moat Framework:**
- **Upper Bound:** Engineering optimizations & fine-tuning.
- **Lower Bound:** Packaging & delivering unoptimized capabilities in user-friendly scenarios.
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## Seede AI — Big Players Should Worry More Than Startups
> **About:** "Code-to-image" — large models generate design through code.
**Yang Mujin, Founder:**
- Stayed up past 3 AM testing Gemini 3.
- **Key leap:** From *layout* (Gemini 2.5) to *design* (Gemini 3) — advanced aesthetics, textures, lighting.
**Advantages:**
- **Aesthetic consistency** — outputs unified design systems vs. chaotic layouts from other models.
- **Code output** — editable layouts maintain user control.
**Startup Strategy:**
Leverage all models, offer **Gemini 3 free for one week** to explore scenarios.
**Note:** Gemini 3 price drop vs. Claude reduces cost significantly.
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## GameSkill — Data Remains the Core Competitive Asset
> **About:** On-device AI coach for personalized gameplay improvement.
**Chen Di, Founder:**
- **Specialized datasets & annotations** maintain edge vs. general models.
- Offers **deep personalization** and **cross-game coaching identity**.
**On-Device Advantages:**
1. **Zero latency & full privacy** — runs locally on GPU/NPU.
2. **Hardware adaptation** — tailored versions for varied PC performance.
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## Hyper3D.AI — Strong Comprehension, But API Learning Still Slow
> **About:** Large model 3D-generation — convert text/image → 3D scenes.
**Zhang Qixuan, CTO:**
- Gemini 3’s “3D generation” mainly covers parametric shapes or voxel code, *not* high-quality assets.
- Valuable as a **planning layer** when combined with true 3D models.
- **Limit:** Needs multiple rounds to learn API calls (~30 min in tests).
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## Soon — Efficiency Boost, Not an Industry Breakthrough
> **About:** Industry-specific model for full-game production pipeline.
**Tan Kai, Founder:**
- Gemini 3 aids in **numerical reasoning**, **tool-call stability**, **long-context handling**.
- Still far from generating complete, editable game loops.
- **Soon’s moat:** Editable, reintegrable assets with CI/CD pipeline integration.
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## Gambo — Real-World Tests Over Hype
> **About:** Game programming Agent — generates full games from text prompts.
**Zhou Zhuoquan, Founder:**
- Visual understanding improved: better fidelity from reference images.
- Rendering still basic — e.g., Street Fighter test produced shapes as characters.
- *Key takeaway:* Both Gemini 3 and Claude 4.5 fail to meet high-quality asset standards for games.
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## Cross-Cutting Insight
Across interviews, **general-purpose model advances** thrill some and leave others unmoved.
Specialized domains still **require targeted data, lower latency, and deeper scenario engineering**.
### Creator Opportunities
Platforms like [AiToEarn官网](https://aitoearn.ai/) enable:
- **AI generation tools integration**
- **Cross-platform publishing** (Douyin, Kwai, WeChat, Bilibili, Facebook, Instagram, LinkedIn, YouTube, Pinterest, X/Twitter, etc.)
- **Analytics & model rankings** ([AI模型排名](https://rank.aitoearn.ai))
Such ecosystems help both startups and individual creators **monetize AI creativity**, even as the line between vertical and general-purpose AI blurs.
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