multimodal benchmark
Flame-VLM-Code
Flame-VLM-Code evaluates multimodal models on visual code generation tasks, measuring ability to generate code from visual inputs such as UI mockups and design specifications.
Updated Aug 11, 2026
Models1
Model coverage1
MetricScore
EvidenceB
Flame-VLM-Code Ranking
Higher score ranks better on this benchmark.
| 1 | ZA | 93.8% | 100.0% | 1 | C |
Flame-VLM-Code Highlights
The leading models and scores on this benchmark.
What is Flame-VLM-Code?
What Flame-VLM-Code measures and how its scores work.
Flame-VLM-Code evaluates multimodal models on visual code generation tasks, measuring ability to generate code from visual inputs such as UI mockups and design specifications.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Flame-VLM-Code
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- flame-vlm-code|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Flame-VLM-Code.
Which model scores highest on Flame-VLM-Code?
GLM-5V-Turbo is currently ranked first with 93.8%.
What does Flame-VLM-Code measure?
Flame-VLM-Code evaluates multimodal models on visual code generation tasks, measuring ability to generate code from visual inputs such as UI mockups and design specifications.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.