Meta Llama 3 Ratings (September 2025)
This page breaks down Meta Llama 3 ratings from all verified review sources to give you a clear, unbiased view of what real users think in September 2025.
We’ve aggregated the latest scores from all major platforms like Trustpilot, G2, Capterra and many more to help you understand Meta Llama 3’s overall reputation. This data-driven overview will show you exactly how Meta Llama 3 is rated - including how it compares to competitors.
Meta Llama 3's Overall Rating Summary
- Average Rating:4.3/5
- Total Reviews:148 reviews
- Sources:G2
- Last updated:September 1, 2025
Meta Llama 3 Ratings by Source
| Platform | Rating | Reviews | Last Update |
|---|---|---|---|
 G2 | 4.3/5 | 148+ reviews | 01.09.25 |
What is Meta Llama 3?
Meta introduces Llama 3, the next generation of its state-of-the-art open-source large language model, featuring pretrained and instruction-fine-tuned models with 8B and 70B parameters. Llama 3 offers improved reasoning, code generation, and instruction following, and will be available on major platforms like AWS, Google Cloud, and Microsoft Azure. Meta AI, built with Llama 3 technology, is designed to help users learn, create content, and connect, with new trust and safety tools like Llama Guard 2, Code Shield, and CyberSec Eval 2.
🤔 Meta Llama 3 vs Competitors: How Do Ratings Compare?
Check out Meta Llama 3 AlternativesFrequently Asked Questions
How trustworthy is Meta Llama 3?
According to G2 review site Meta Llama 3 holds rating of 4.3/5, indicating that users consistently find value and reliability in the platform as of September 2025.
How many stars is Meta Llama 3 rated?
Meta Llama 3 has an average star rating of 4.3 out of 5 stars based on average of 148 reviews as of September 2025.
Where does the rating data come from?
The ratings are pulled from Meta Llama 3 public reviews pages on platforms: G2. We update these ratings monthly to ensure they reflect the most current customer feedback.
How overall average rating for Meta Llama 3 is calculated?
The overall average rating is calculated by taking the weighted average of all ratings, using the total reviews count from each platform as the weight.