ERNIE-Image-Turbo 8B: Comprehensive Multi-Model Comparison with Prompt Examples

Baidu has just open-sourced an 8B-parameter text-to-image model called ERNIE-Image. When comparing text-to-image models, we always instinctively compare parameter counts. Parameter count doesn't directly demonstrate a model's capabilities and strengths, but we still believe that "size matters" — parameter count represents potential, while real capability depends on training quality. This article makes no objective judgments; we let the benchmarks speak.

Open-Source Text-to-Image Model Parameter Rankings

Parameter comparison

Here's a ranking of open-source text-to-image models as of today, sorted by parameter count:

HunyuanImage-3.0 (Tencent Hunyuan) — 80B total parameters (MoE, 64 experts, ~13B active): Currently the largest open-source T2I MoE model, native multimodal autoregressive architecture, excels at complex prompts, world knowledge reasoning, Chinese/English text rendering and knowledge-dense generation. Suitable for high-quality, professional scenarios, but inference requires high-end hardware (datacenter-grade, quantizable). Open-sourced September 2025, weights available on HuggingFace.
FLUX.2 [dev] (Black Forest Labs) — 32B parameters: The open-source version of the FLUX.2 series, supporting T2I, image editing, and multi-reference image fusion. Rectified flow transformer architecture with exceptional prompt following, detail and coherence. Runs on consumer GPUs (with quantization/FP8 optimization), one of the 2026 open-source flagships.
FLUX.1 [dev/schnell] — ~12B parameters: (Early FLUX.1 series) Classic DiT/flow matching model with top-tier prompt following and text rendering. Schnell is the distilled fast version. Largest community ecosystem, comprehensive ComfyUI support.
Stable Diffusion 3.5 Large (Stability AI) — 8.1B parameters (MMDiT): SD series latest main model, significantly improved prompt following and layout, supports 1MP+ resolution. Medium variant at 2.5B parameters is more suitable for consumer hardware. Largest open-source community, mature LoRA/fine-tuning ecosystem.
Qwen-Image / Qwen-Image-2.0 (Alibaba Qwen) — ~7B–20B parameters: (2.0 unified to ~7B, lightweight and efficient) Strong Chinese/multilingual text rendering, professional layout (supports 1K token long prompts), native 2K resolution. Version 2.0 unifies generation + editing with high efficiency, ideal for Asian languages and infographics.
Z-Image-Turbo / Other compact efficient models — ~6B parameters: Efficient real-time/edge deployment models, fast speed, suitable for low-resource environments.

So in terms of parameter count, Baidu's ERNIE-Image is actually not that large — it sits in the middle. As for image performance, let the pictures speak.

ERNIE-Image Overview

ERNIE-Image is an open text-to-image model developed by Baidu's ERNIE-Image team. It is based on a single-stream diffusion transformer (DiT) with 8B parameters, using a latent diffusion model (LDM) framework, equipped with a lightweight prompt enhancer that expands brief inputs into richer, more structured prompts, better unlocking model capabilities. With just 8B DiT parameters, ERNIE-Image achieves state-of-the-art performance among open-weight text-to-image models — it focuses not just on visual appeal but on controllability: accurate content representation matters as much as aesthetics. In practice, it excels at complex instruction following, precise text rendering, and structured image generation — areas where many existing open-weight models still fall short.

Model architecture

Model Benchmark Comparisons (Official)

Official benchmarks

Built-in Prompt Enhancement

ERNIE-Image performs best with long, detailed and well-structured prompts — richer descriptions generally yield better generation quality, tighter instruction fidelity, and more faithful rendering of complex layouts or narrative content. But in practice, users tend to enter short sentences rather than the detailed prompts that play to the model's strengths.

To bridge this gap, we released a built-in 3B prompt enhancer that expands brief user inputs into more detailed, structured prompts better suited for ERNIE-Image. The goal isn't to change user intent but to transform concise requests into a form that better leverages the model's value — especially in posters, anime, web layouts, game screenshots and other structured visual tasks.

The examples below illustrate this effect. Without prompt enhancement, the model tends to interpret short prompts literally and incompletely. With our 3B enhancer, prompts become more descriptive and structured, significantly improving results in many scenarios. We've also found that stronger large language models can push this further — suggesting that prompt enhancement is a practical lever for leveraging ERNIE-Image's long-prompt generation capability.

Prompt enhancer effect

Prompt enhancer effect 2

Prompt enhancer effect 3

Prompt enhancer effect 4

Prompt enhancer effect 5

Prompt enhancer effect 6

Replicating Official Prompts

Online demo: https://huggingface.co/spaces/baidu/ERNIE-Image-Turbo

HuggingFace demo

Prompt Practice: OREO Polymer Clay Miniature

This prompt is quite complex:

OREO official result 1

OREO official result 2

Full prompt:

A studio macro photography shot of a handcrafted polymer clay-textured miniature diorama. Centered in the frame is a small Oreo-themed shop in vertical composition. The roof is built from several giant Oreo cookies arranged in a cross pattern — deep black with thick white cream layers, classic embossed texture and clear 'OREO' lettering, with handmade clay rounded texture and subtle fingerprint details. The shop front has an open wooden serving window, above which hangs a prominent blue rectangular sign with bold 3D white uppercase letters reading 'OREO'. At the window, a tiny clay shopkeeper in a blue apron and white work cap leans forward, holding a small Oreo cookie to hand out the window. Outside stands a customer — a miniature clay figure wearing a yellow backpack and red casual jacket, looking up slightly with both hands extended to receive the cookie. The muddy ground around the shop is densely scattered with Oreos of various sizes — some intact, some broken open revealing white filling, covering the entire foreground and surrounding area. The scene uses soft studio lighting, even and warm, highlighting the matte细腻 texture of polymer clay. Extremely shallow depth of field with precise focus on the shopkeeper, customer and sign area, while foreground cookies and background edges show strong smooth bokeh, creating a perfect miniature-world scale and dreamy atmosphere.

Baidu ERNIE-Image Replication

OREO ERNIE replication 1

OREO ERNIE replication 2

Z-Image Replication

OREO Z-Image 1

OREO Z-Image 2

FireRed Qwen-image-2512

OREO FireRed 1

OREO FireRed 2

FLUX2

OREO FLUX2

Nanobana 2 Pro

OREO Nanobana

Jimeng (即梦)

OREO Jimeng 1

OREO Jimeng 2

Multi-Text Combination Test

Prompt:

A vertically composed cartoon hand-drawn style infographic on soft beige-white background with subtle paper texture, well-spaced layout with generous whitespace. Overall uses marker pen and colored pencil mixed hand-drawn texture lines, no photorealistic elements. Centered at the top is a prominent hand-drawn speech bubble containing handwritten bold title text 'Pomodoro Technique'. To the left of the title is an anthropomorphic cartoon red tomato character wearing round black-framed glasses, smiling while holding a pointer. Directly below the title is a smaller subtitle 'Efficient Time Management Guide'. The main content is divided into four step blocks, connected by hand-drawn dashed black arrows from top to bottom: Block 1 shows a red target icon with dart on the left and handwritten text '1. Set Goals' with body text 'Pick one task to complete, keep it clear.' Block 2 alternates to the right with a classic tomato-shaped mechanical timer icon (set to 25), left text '2. Focus for 25 minutes' with body 'Work with full concentration, block all distractions.' and yellow highlight on '25 minutes'. Block 3 on the left has a steaming coffee cup sketch, right text '3. Short Break' with 'When alarm rings, rest 5 minutes, drink water or stretch.' Block 4 on the right shows four neatly arranged small tomato icons and green single sofa, left text '4. Long Break' with 'After completing four Pomodoro cycles, take 15-30 minute deep relaxation.' At the bottom is a glowing yellow cartoon light bulb icon with blue handwritten note 'Tip: During focus periods, silence your phone and keep it out of sight!' Bright and cheerful color scheme dominated by red, bright yellow and soft sky blue.