StableLM
Reviews
Star rating
Rank in Small Language Models (SLMs)
Pros and cons
Pros
- Efficiency
- Ease of Use
- Performance Improvement
- Helpful
- Accuracy
- Content Creation
Cons
- Technical Issues
- Data Security
- Low Accuracy
- High Resource Consumption
- Slow Performance
- Improvement Needed
Traffic & LLM citations
Source: G2 review data
Winning from
Key stats
Adoption by company size
| Segment | Share of reviews |
|---|---|
| Small Business | 50.0% |
| Mid-Market | 22.7% |
| Enterprise | 27.3% |
Quarterly history
| Quarter | Reviews | Star rating |
|---|---|---|
| 2025 Q4 | 5 | 4.5 |
| 2026 Q2 | 2 | 4.8 |
| 2026 Q3 | 2 | 4.3 |
Satisfaction ratings
What reviewers say
Open, Flexible, and GreaFlexible and Useful AI for Everyday Taskst for Custom AI Experimentation
“What I like most about StableLM is how open and flexible it is. It gives me more control over how I use and customize the model, and it’s especially helpful for experimenting with different AI projects without feeling locked into a closed platform.”
StableLM’s Open-Source Flexibility Gives Developers More Control
“StableLM is open source and flexible for experimentation. It gives developers more control over how the model is used and integrated into their application.”
Flexible Control for Experimenting with StableLM Model Workflows
“I like the flexibility StableLM gives me when working with language model projects. It is useful for testing text generation workflows, experimenting with different model sizes, and adapting models for specific machine learning tasks. I also appreciate having more control over th”