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Models/3D/Tripo 1.4
Tripo logoTripo·3D Generation

Tripo 1.4

View rankingstripo3d.ai
ReleasedJun 2024

Tripo 1.4 is a high-performance 3D generative model developed by Tripo (VAST AI Research) designed to convert text prompts and 2D images into high-quality 3D assets. Building on the company's research into 3D scaling laws and large-scale reconstruction models (LRM), version 1.4 introduced significant improvements in geometric fidelity and multi-view consistency compared to its predecessors. It is optimized for speed, often generating base 3D meshes in seconds to facilitate rapid prototyping and creative workflows.

One of the defining features of Tripo 1.4 is its support for multi-view generation, allowing the model to integrate visual information from several angles to produce more accurate and detailed 3D structures. The architecture is capable of outputting production-ready assets with physically-based rendering (PBR) textures and refined topology. This makes it suitable for diverse industries, including gaming, 3D printing, and architectural visualization.

Capabilities and Performance

The model supports a dual-input workflow: Text-to-3D, which transforms natural language descriptions into 3D meshes, and Image-to-3D, which reconstructs objects from single or multiple reference photos. Tripo 1.4 is noted for its ability to generate multiple model variations from a single prompt, providing users with a selection of geometric interpretations. It produces watertight meshes that can be exported in industry-standard formats such as GLB, OBJ, and STL.

For optimal results, users are encouraged to use clear, well-lit reference images with high contrast between the subject and the background. When utilizing text prompts, detailed descriptions of materials, lighting, and specific geometric features help the model better capture the intended design. While the model handles complex shapes, single-subject inputs generally yield the highest structural coherence.

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How Tripo 1.4 ranks

Tripo 1.4 is highlighted in the table below. Switch the metric to see how the ordering changes.

Crafiq's community-driven 3D generation quality arena using ELO ratings from pairwise comparisons. Data from Crafiq 3D Arena

#
1
TencentTencent
Tencent
Hunyuan3D 3.1
Tencent
1,757±11038$0.16Feb 2026
2
TripoTripo
Tripo
Tripo H3.1
Tripo
1,719±13625$0.4Mar 2026
3
MeshyMeshy
Meshy
Meshy 6
Meshy
1,592±11833$0.8Oct 2025
4
MicrosoftMicrosoft
Microsoft
TRELLIS.2open weights
Microsoft
1,590±11833$0.35Dec 2025
5
Hyper3DHyper3D
Hyper3D
Rodin 2.5
Hyper3D
1,573±18214$0.4May 2026
6
TripoTripo
Tripo
Tripo P1
Tripo
1,520±13127$0.4Mar 2026
7
TencentTencent
Tencent
Pixal3Dopen weights
Tencent
1,504±18214$0.42May 2026
8
TripoTripo
Tripo
Tripo 2.5
Tripo
1,502±12032$0.4Jan 2025
9
TencentTencent
Tencent
Hunyuan3D 2.1open weights
Tencent
1,498±12032$0.16Jun 2025
10
BytedanceBytedance
Bytedance
Seed3d
Bytedance
1,498±11336$0.33Oct 2025
11
MeshyMeshy
Meshy
Meshy 5
Meshy
1,475±11833$0.4Aug 2025
12
MicrosoftMicrosoft
Microsoft
TRELLISopen weights
Microsoft
1,430±10641$0.02Dec 2024
13
Hyper3DHyper3D
Hyper3D
Rodin 2
Hyper3D
1,393±11535$0.4Oct 2025
14
TencentTencent
Tencent
Hunyuan3d 2open weights
Tencent
1,356±11038$0.08Jan 2025
15
TripoTripo
Tripo
TripoSRopen weights
Tripo
1,206±11535$0.07Mar 2024
16
TencentTencent
Tencent
Hunyuan3d 3
Tencent
—0—Sep 2025
17
Hyper3DHyper3D
Hyper3D
Rodin 1.5
Hyper3D
—0—Apr 2025
18
TencentTencent
Tencent
Hunyuan3D 2 Turbo
Tencent
—0—Mar 2025
19
TencentTencent
Tencent
Hunyuan3d 2 Mini Turboopen weights
Tencent
—0—Mar 2025
20
TencentTencent
Tencent
Hunyuan3d 2 Mini
Tencent
—0—Mar 2025
21
TripoTripo
Tripo
TripoSGopen weights
Tripo
—0—Feb 2025
22
MeshyMeshy
Meshy
Meshy 4
Meshy
—0—Aug 2024
23
TripoTripo
Tripo
Tripo 1.4
Tripo
—0—Jun 2024
24
OpenAIOpenAI
OpenAI
Shap-Eopen weights
OpenAI
—0—May 2023

Global Crafiq 3D Arena data from Crafiq 3D Arena