Kreat3D vs Snorkel AI
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Kreat3D compared with Snorkel AI
| Detail | 
Kreat3D | 
Snorkel AI |
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| What it does | Turn text prompts into textured 3D models online
| Expert data development for frontier AI
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| Stage | Not given
| Established
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| Founded | Not given
| 2019
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| Based in | Not given
| Not given
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| Pricing model | Freemium
| Contact for pricing
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| Pricing | Free: 100 credits ($0/mo). Pro: 500 credits/month ($9/mo billed yearly at $108/year). Max: 1,500 credits/month ($25/mo billed yearly at $299/year). Ultra: 5,500 credits/month ($83/mo billed yearly at $999/year).
| Not given
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| Key features | - Generate 3D models from text prompts describing shape, material, and style
- Export to GLB, OBJ, FBX, and STL formats
- Choose between textured and geometry-only output
- Inspect and preview models in browser before exporting
- Multiple interface options: Studio, Canvas, MCP, and CLI
- Regenerate variations and refine surfaces with texture and remesh tools
- Commercial usage rights for paid plan subscribers
- Cloud-based generation without needing 3D modeling software
| - Research-grade datasets with rubrics, reviewer guidance, difficulty tiers and eval slices
- Custom data development for specific failure surfaces and use cases
- Specialized agents built on expert data evaluated in real workflows
- Benchmark-grade environments and evaluation harnesses
- Provenance tracking with full audit trails for all labeled data
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| What makes it different | - No 3D modeling experience required - works from text descriptions alone
- Supports multiple workflows including browser, visual canvas, AI agent, and CLI
- Free tier with starter credits requires no credit card
- Supports industry-standard export formats for games, 3D printing, and design tools
- Integrated texture and remesh tools for iterating on generated models
| - Research-driven data lab focused on quality and frontier-hardness rather than volume
- Domain-specific benchmarks and evaluation environments built for real-world, high-stakes failures
- Research methodology published and peer-reviewed with 200+ papers
- Comprehensive data lifecycle from SFT to RL training to evaluation
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 7 ▼ −1 (down) since last check | 72 ● no change since last check |
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| Trust Flow (Majestic) | 6 | 24 |
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| Citation Flow (Majestic) | 28 | 42 |
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| Referring domains (Majestic) | 47 | 2315 |
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4 details filled in for both companies.
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