When you type "show me monthly revenue by region" into an AI dashboard tool, something complex happens behind the scenes.
The AI model must understand your business intent, identify the correct data columns, select an appropriate chart type, and generate valid configuration.
Different models handle these tasks very differently. Some get the chart type right but use wrong columns. Others understand the intent but produce invalid output.
We wanted real answers. So we tested 12 popular models across 32 real-world business scenarios.
What We Tested
We designed 32 test scenarios covering common business analytics requests:
Basic charts: Bar, line, pie, area for standard KPIs
Multi-dimensional analysis: Grouped comparisons, stacked charts
Time-series analysis: Trends over time, period comparisons
Conditional formatting: Thresholds, color rules
Multilingual prompts: Requests in Turkish and English
Complex queries: Multi-step analysis with follow-up questions
Each model was scored on correctness (right chart type and data mapping), completeness (all requested elements included), speed (response time), and stability (consistent results across similar prompts).
Speed Rankings
Response time matters for interactive use. If users wait more than 10 seconds, engagement drops.
| Model | CPU (no GPU) | GPU / Apple Silicon |
|---|---|---|
| Gemma 4 E2B | ~5s | ~1.5s |
| Mistral 7B | ~6s | ~2s |
| Qwen 2.5 7B | ~7s | ~2s |
| Llama 3.1 8B | ~8s | ~2s |
| Qwen 3 8B | ~10s | ~3s |
Gemma 4 E2B is clearly the fastest — ideal for interactive chart creation where speed matters more than the last few percent of accuracy.
Chart Accuracy (32 Scenarios)
| Model | Correct | Wrong | Partial |
|---|---|---|---|
| Llama 3.1 8B | 28/32 | 2 | 2 |
| Qwen 2.5 7B | 27/32 | 3 | 2 |
| Qwen 3 8B | 26/32 | 3 | 3 |
| Gemma 4 E2B | 25/32 | 4 | 3 |
| Mistral 7B | 24/32 | 5 | 3 |
Llama 3.1 8B leads in accuracy. But the gap between top models is narrowing with each release.
Multilingual Performance
For teams working in multiple languages, this matters a lot.
| Model | Turkish Prompts | English Prompts | Overall |
|---|---|---|---|
| Qwen 2.5 7B | 26/32 | 27/32 | Best multilingual |
| Qwen 3 8B | 25/32 | 26/32 | Strong multilingual |
| Llama 3.1 8B | 22/32 | 28/32 | English-first |
| Gemma 4 E2B | 20/32 | 25/32 | Weaker Turkish |
| Mistral 7B | 19/32 | 24/32 | Weaker Turkish |
Qwen models clearly dominate multilingual scenarios. If your team works in Turkish, Arabic, or other non-English languages, Qwen should be your first choice.
What We Learned About Chart Generation
Intent Detection Is Critical
"Show me revenue by region" could be a bar chart, pie chart, or treemap. The best models infer the most appropriate visualization type from context.
Structured Output Matters
Some models generate conversational text when chart configuration is expected. Others produce partial configurations that break rendering. This is the most common failure mode.
Edge Cases Cause Failures
Common patterns:
- Misidentifying date columns as categorical data
- Generating chart types that don't match data structure
- Failing to handle empty or null values
- Confusing similar column names
Better models handle these edge cases gracefully.
Consistency Across Sessions
Some models produce different charts for identical prompts across sessions. For production dashboard generation, consistency is essential.
Recommended Models by Use Case
| Use Case | Recommended Model | Why |
|---|---|---|
| Turkish/multilingual dashboards | Qwen 2.5 7B | Best multilingual support |
| Fast interactive use | Gemma 4 E2B | Quickest response time |
| Maximum accuracy | Llama 3.1 8B | Highest chart correctness |
| Balanced performance | Qwen 3 8B | Good accuracy + multilingual |
| Lightweight deployment | Mistral 7B | Low hardware requirements |
The Gap Is Narrowing
Models that struggled with chart generation six months ago now produce acceptable results. Within the next year, most mainstream models will handle business chart generation competently.
For now, selecting the right model for your specific use case still matters.
We built LivChart to make local AI dashboards accessible. Try different models and see which works best for your data.
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