StableLM 3B vs StableLM 3B Multimodal
Comprehensive side-by-side comparison of pricing, performance benchmarks, and capabilities
At a Glance
Best Overall Performance
StableLM 3B Multimodal
Higher overall benchmarks
Best for Coding
StableLM 3B Multimodal
74% coding score
Best for Reasoning
StableLM 3B Multimodal
75% reasoning score
Best MMLU Score
StableLM 3B Multimodal
76% general knowledge
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Detailed Comparison
| Feature | StableLM 3B | StableLM 3B Multimodal | Winner |
|---|---|---|---|
| Provider | Stability AI | Stability AI | — |
| Context Window | 8k | 16k | — |
|
MMLU Score
General knowledge & reasoning | 75% | 76% | StableLM 3B Multimodal |
|
Coding Score
Code generation & debugging | 72% | 74% | StableLM 3B Multimodal |
|
Reasoning Score
Logic & problem-solving | 74% | 75% | StableLM 3B Multimodal |
| Release Date | 2023 | 2025 | — |
| Vision Support | — | ✓ Yes | — |
| Function Calling | ✓ Yes | ✓ Yes | — |
Performance Comparison
MMLU (General Knowledge)
Difference: 1.0%Coding Performance
Difference: 2.0%Reasoning & Logic
Difference: 1.0%Expert Analysis
Performance Analysis
StableLM 3B Multimodal outperforms across 1 of 3 benchmarks, with particularly strong coding abilities (74%).
Final Verdict
Our comprehensive recommendation based on all factors
Both models show comparable coding performance, with less than 5 points separating them on benchmark tests. The optimal choice between these models depends on your specific use case and performance requirements.
Our Recommendation
Choose StableLM 3B Multimodal for applications where response quality directly impacts business outcomes, or evaluate both models based on your specific use case requirements.
Best For These Use Cases
StableLM 3B Excels At:
- Creative content generation
- Research assistants
- Self-hosted experimentation
- Lightweight chatbots
- Prototype testing
StableLM 3B Multimodal Excels At:
- Multimodal research
- Prototype AI assistants
- Creative content
- Fine-tuning experiments
- Lightweight agents
Strengths & Weaknesses
StableLM 3B
Strengths
- • Open weights
- • Easy fine-tuning
- • Good creative outputs
- • Community-driven
Considerations
- • Short context
- • Limited multimodal support
- • Moderate reasoning
- • Fewer enterprise tools
StableLM 3B Multimodal
Strengths
- • Open weights
- • Multimodal support
- • Lightweight
- • Creative generation
Considerations
- • Limited context
- • Moderate reasoning
- • Smaller model
- • Not enterprise-ready
Frequently Asked Questions
Which is better: StableLM 3B or StableLM 3B Multimodal?
StableLM 3B Multimodal offers superior overall performance with higher benchmark scores across MMLU, coding, and reasoning tests. The best choice depends on your specific use case requirements and performance priorities.
What are the key differences?
StableLM 3B Multimodal leads in overall performance with higher benchmark scores, while StableLM 3B may offer advantages in specific areas like context window size or specialized capabilities. Both models have their strengths depending on your particular needs.
Which is better for coding?
StableLM 3B Multimodal leads in coding performance with a score of 74%, making it 2.0 percentage points better than StableLM 3B. This makes StableLM 3B Multimodal the superior choice for software development, code generation, and debugging tasks.
Can I use both models together?
Yes! Many organizations use multiple models strategically: one model for routine tasks where efficiency matters, and another for complex, mission-critical applications requiring maximum accuracy. This hybrid approach optimizes both performance and resource utilization across different use cases.
How often are these benchmarks updated?
We update all benchmark scores and pricing data daily to reflect the latest model versions and API pricing changes. Benchmark scores are sourced from official documentation, independent testing platforms like Artificial Analysis, and peer-reviewed academic evaluations. Last updated: 2/2/2026.
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