Model reference · open weights
Qwen-Image-Bench is an open-weight language model from Qwen, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Q-Judger A fine-tuned judge model for evaluating text-to-image (T2I) generation quality. Built on top of Qwen3.6-27B, it scores generated images across 5 hierarchical dimensions using structured checklists and outputs JSON-formatted evaluation results. Links Model Description Q-Judger is a vision-language model fine-tuned specifically for automated evaluation of text-to-image generated images. Given a text prompt and a generated image, the model evaluates the image on fine-grained quality criteria organized in a 3-level hierarchy and outputs structured JSON scores. - Base Model: Qwen3.6-27B - Task: Image quality evaluation / judging - Input: Text prompt + generated image - Output: Structured JSON with per-dimension scores (0 = Fail, 1 = Pass, 2 = Excel, N/A) - Thinking Mode: Enabled — the model uses chain-of-thought reasoning before producing the final JSON output Evaluation Dimensions The model evaluates images across 5 top-level dimensions, each with multiple sub-dimensions: Quality - Realism: Physical Logic, Material Texture - Detail: Noise, Edge Clarity, Naturalness - Resolution: Resolution Aesthetics - Composition: Composition - Color Harmony: Color Harmony - Lighting: Lighting & Atmosphere - Anatomical Portraiture: Anatomical Fidelity - Emotional Expression: Emotional Expression - Style Control: Style Control Alignment - Attributes: Quantity, Facial Expression, Material Properties, Color, Shape, Size - Actions: Contact Interaction, Non-contact Interaction, Full-body Action - Layout: 2D Space, 3D Space - Relations: Composition Relationship, Difference/Similarity, Containment - Scene: Real-world Scene, Virtual Scene Real-world Fidelity - Fairness: Social Bias, Cultural Fairness - Safety & Compliance: Safety & Compliance - World Knowledge: Animals, Objects, Information Visualization, Temporal Characteristics, Cultural Elements Creative Generation - Imagination: Imagination - Feature Matching: Feature Matching - Logical Resolution: Logical Resolution - Text Rendering: Text Accuracy, Text Layout, Font, Cross-lingual Generation - Design Applications: Graphic Design, Product Design, Spatial Design, Fashion Styling, Game Design, Art Design - Visual Storytelling: C
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | Qwen |
|---|---|
| Type | Language models |
| Parameters (lead) | 27.4B |
| Variants | 1 |
| Runs with | transformers |
| Based on | Qwen/Qwen3.6-27B |
| Released | 2026-05-21 |
| Popularity | 43k downloads / month |
| Likes | 93 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| Qwen-Image-Bench | 27.4B | BF16 | ~62.9 GB | — | Weights ↗ |
Using it via the API
Once AxForge deploys qwen-image-bench for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen-image-bench below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"qwen-image-bench","messages":[{"role":"user","content":"Hello"}]}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗