In the rapidly evolving world of AI, open-source models are gaining traction as alternatives to proprietary solutions. Today, we’re taking a closer look at Zamba2 7B Instruct, an open-source model that’s making waves in the AI community.
The Basics
Zamba2 7B Instruct is an impressive model that can be run locally, provided you have sufficient VRAM. In our test, it only consumed about 63% of a 24GB VRAM setup, making it accessible for many high-end consumer-grade GPUs.
Putting It to the Test
To evaluate Zamba’s capabilities, we challenged it with a complex task: creating a Falling Sand game. Here’s what we found:
- Initial Implementation: The model managed to create a basic simulation, but with a quirk – the sand fell to the left instead of downwards.
- Refinements: We requested improvements such as adding water, plants, fire, element switching via number keys, and mouse support for adding elements.
- Results: The model made some progress. We observed a sand particle being added, which is a step in the right direction. However, the overall implementation fell short of our expectations.
Comparison to Other Models
While Zamba2 7B Instruct shows promise, it still has a way to go before it can compete with more established models:
- It performs better than the proprietary “liquid foundation” models.
- However, it lags behind other open-source models like Llama 3.2.
- When compared to advanced models like Claude, the gap in performance is even more noticeable.
The Verdict
Zamba2 7B Instruct’s biggest advantage is its ability to run locally with a reasonable amount of VRAM. This makes it accessible to developers and researchers who prefer or need to work with models on their own hardware.
However, as a coding assistant, it still has significant room for improvement.