GLM-Image vs Ovis-Image-7B vs FLUX.2 Dev Turbo: 5 Prompt Test
GLM-Image vs Ovis-Image-7B vs FLUX.2 Dev Turbo: 5 Prompt Text-to-Image Test
GLM-Image vs Ovis-Image-7B vs FLUX.2 Dev Turbo face the same five prompts. This test focuses on text rendering, labels, and layout in images. The results show where each model performs best.
What this test covers
A consistent set of five prompts ran on each model. Each prompt targets a practical use case: posters, product photos, street signage, UI mockups, and handwritten menus. The same prompts let direct visual comparison.
Models tested
GLM-Image
GLM-Image generates images from text and supports image edits. The model uses a hybrid autoregressive plus diffusion decoder to improve complex layouts and text rendering. Model page: https://wiro.ai/models/zai-org/glm-image
Ovis-Image-7B
Ovis-Image-7B targets compact, high fidelity text rendering. The model fits smaller deployments while keeping high word accuracy for banners and UI. Model page: https://wiro.ai/models/aidc-ai/ovis-image-7b
FLUX.2 Dev Turbo
FLUX.2 Dev Turbo focuses on photoreal detail and asset consistency. The model runs fast and keeps product and character details stable across edits. Model page: https://wiro.ai/models/wiro/flux-2-dev-turbo
Test prompts
- Prompt 1: Minimalist Swiss style poster for a bicycle repair shop. White background. Big headline text: NIGHT OWL BIKE CO. Smaller subhead text: 24 7 REPAIRS. Simple line art bicycle icon. Lots of whitespace. Crisp print layout.
- Prompt 2: Photorealistic studio shot of a glass jar of honey with a paper label. Label text: ACACIA HONEY. Small line: NET 250G. Warm softbox lighting. Shallow depth of field. Clean beige background.
- Prompt 3: Cinematic photo of a busy street food stall at dusk in Seoul. Wet pavement with rain reflections. Neon signage. Main sign text: TTEOKBOKKI. Smaller sign text: SPICY RICE CAKES. People in motion blur. High detail.
- Prompt 4: Isometric UI mockup of a mobile app onboarding screen. Clean modern flat design. Pastel gradient background. Big title text: TRACK YOUR HABITS. Button text: GET STARTED. Minimal icons and charts. High readability.
- Prompt 5: Realistic chalkboard cafe menu. Title text: MORNING MENU. Eight items with prices, all legible: ESPRESSO 3, LATTE 4, CAPPUCCINO 4, CROISSANT 3, BAGEL 2, GRANOLA 5, TEA 2, JUICE 4. Handwritten chalk style. Soft vignette lighting.
Results
Prompt 1 — Swiss poster
| GLM-Image | Ovis-Image-7B | FLUX.2 Dev Turbo |
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Prompt 2 — Product photo
| GLM-Image | Ovis-Image-7B | FLUX.2 Dev Turbo |
|---|---|---|
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Prompt 3 — Street food signage
| GLM-Image | Ovis-Image-7B | FLUX.2 Dev Turbo |
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Prompt 4 — UI mockup
| GLM-Image | Ovis-Image-7B | FLUX.2 Dev Turbo |
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Prompt 5 — Chalkboard menu
| GLM-Image | Ovis-Image-7B | FLUX.2 Dev Turbo |
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Quick comparison
| Model | Approx runtime (1024×768) | Best for |
|---|---|---|
| GLM-Image | ~60 s | Dense text and layout tasks, complex diagrams and posters |
| Ovis-Image-7B | ~25 s | Fast bilingual text rendering for banners and UI |
| FLUX.2 Dev Turbo | ~15 s | Photoreal product shots and asset consistency |
Verdict
GLM-Image gives the best results on dense, information rich prompts. Ovis-Image-7B balances speed with very clean bilingual text rendering. FLUX.2 Dev Turbo runs fastest and produces the most photoreal images and consistent assets. Each model fits a clear use case. Try the models on Wiro at their model pages below.
Try the models: GLM-Image — Ovis-Image-7B — FLUX.2 Dev Turbo