- - 🆕 Distilled, speed-optimized text-to-image model from the Tongyi-MAI team
- - 📏 6-billion-parameter single-stream diffusion transformer (S3-DiT)
- - ⚡ Sub-second inference on H800 GPUs using only 8 NFEs
- - 🔧 Designed to fit within 16GB VRAM on consumer cards
- - 🌐 Bilingual English–Chinese text rendering
- - 🎯 Generates images up to 1024x1024 resolution
- - 🔒 Open weights under the Apache 2.0 license
- - 📚 Roughly 919K downloads on Hugging Face
Z.ai, formally Knowledge Atlas Technology Joint Stock Co., Ltd., is a Chinese technology company specializing in artificial intelligence. Previously known internationally as Zhipu AI, the company rebranded to Z.ai in 2025. Its core focus is the GLM family of large language…
Explore 17 more models by Z.ai →Z-Image Turbo is the fast, distilled variant in the Z-Image image-generation family, published on Hugging Face by the Tongyi-MAI team with open weights under the Apache 2.0 license. It is a 6-billion-parameter text-to-image model built on a Scalable Single-Stream Diffusion Transformer (S3-DiT) architecture, generating images up to 1024x1024 resolution.
The defining characteristic is efficiency. Where the full Z-Image foundation model runs many diffusion steps with classifier-free guidance, the Turbo edition is distilled to produce output in only 8 Number of Function Evaluations, with guidance scale set to zero. According to the maintainer's model card, this enables sub-second inference latency on enterprise-grade H800 GPUs while still fitting comfortably within 16GB of VRAM on consumer devices, trading some pose diversity and aesthetic richness for speed.
Compared with the non-distilled Z-Image, the Turbo variant is positioned for rapid iteration and real-time use rather than maximum quality and diversity, making it suited to local deployment and high-throughput pipelines. It supports bilingual English–Chinese text rendering and includes a prompt enhancer for improved instruction following.
The maintainer reports Elo-based human-preference evaluation via the Alibaba AI Arena. The weights are freely available on Hugging Face, and the Apache 2.0 license permits commercial use with attribution.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
| Seller | Reputation↓ | Routing | $ / img | Categories | API |
|---|---|---|---|---|---|
| Venice.ai Proxy 0x1f22…18c9 | 100.00 | #2 | $0.005 | image,creative | openai-images |
| ▲ Apex Ant 0x73b4…e736 | 91.01 | #1 | $0.004 | image,media | openai-images |
| D5V1N2 0xd5e7…7be0 | 33.17 | gated | $0.012 | image,creative,fast,router,fallback | openai-images |
"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = on-chain trust (0-100). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.