Amber
by LLM360
Fully open model with complete training process transparency.
Quick Facts
- Model Size
- 7B
- Context Length
- 2K tokens
- Release Date
- Dec 2023
- License
- Apache 2.0
- Provider
- LLM360
- KYI Score
- 7.2/10
Best For
Performance Metrics
Speed
Quality
Cost Efficiency
Specifications
- Parameters
- 7B
- Context Length
- 2K tokens
- License
- Apache 2.0
- Pricing
- free
- Release Date
- December 11, 2023
- Category
- llm
Key Features
Pros & Cons
Pros
- ✓Complete transparency
- ✓Reproducible
- ✓Apache 2.0
- ✓Research-friendly
Cons
- !Research focus
- !Shorter context
- !Not optimized for production
Ideal Use Cases
Research
Education
Transparency studies
Experimentation
Amber FAQ
What is Amber best used for?
Amber excels at Research, Education, Transparency studies. Complete transparency, making it ideal for production applications requiring llm capabilities.
How does Amber compare to other models?
Amber has a KYI score of 7.2/10, with 7B parameters. It offers complete transparency and reproducible. Check our comparison pages for detailed benchmarks.
What are the system requirements for Amber?
Amber with 7B requires appropriate GPU memory. Smaller quantized versions can run on consumer hardware, while full precision models need enterprise GPUs. Context length is 2K tokens.
Is Amber free to use?
Yes, Amber is free and licensed under Apache 2.0. You can deploy it on your own infrastructure without usage fees or API costs, giving you full control over your AI deployment.
Related Models
LLaMA 3.1 405B
9.4/10Meta's largest and most capable open-source language model with 405 billion parameters, offering state-of-the-art performance across reasoning, coding, and multilingual tasks.
LLaMA 3.1 70B
9.1/10A powerful 70B parameter model that balances performance and efficiency, ideal for production deployments requiring high-quality outputs.
BGE M3
9.1/10Multi-lingual, multi-functionality, multi-granularity embedding model.