Llama 3 vs. Llama 3.1: Which is better for your AI products?

In July 2024, Meta released its latest advanced model, Lama 3.1 with 405 billion parameters, along with smaller versions Lama 3.1 70B and Lama 3.1 8B. This release took place only three mohs after the iroduction of Lama 3. While Llama 3.1 405B outperforms GPT-4 and Opus Cloud 3 in most metrics, making it the most powerful open-source model available, it may be slow to generate and has high first-token time (TTFT) for many real-world applications. Not really a good choice.

For developers looking to iegrate these models io production or self-host them, Lama 3.1 70B appears to be a more viable alternative. But how does it compare to its predecessor, the Lama 3 70B? Is it worth the upgrade if you’re already using the Lama 3 70B in production?

The main improvemes in the new Lama model:

• Text window: Lama 3.1 70B with 128K vs 8K Lama 3 70B (16x increase)
• Maximum output token: 4096 vs 2048 (doubled)

These dramatic improvemes in text windowing and output capacity give the Lama 3.1 70B a significa advaage in handling longer and more complex tasks, despite both models having the same parameter cou, price, and knowledge cut-off date. Extensive capabilities make the Lama 3.1 70B more versatile and powerful for a wide range of applications.

Comparison of criteria

Performance comparison

We conducted evaluation tests on the Keywords AI platform. This evaluation consisted of three parts:

• Code developme: Both models were able to successfully perform code developme tasks for fro-end and back-end. Lama 3 70B often produced more concise and readable solutions.
• Docume processing: Both models achieved high accuracy (~95%) in processing documes from 1 to 50 pages. The Lama 3 70B showed much higher processing speed but was limited to documes under 8-10 pages due to the smaller text window. The Lama 3.1 70B, although slower, could handle much longer documes.
• Logical reasoning: Llama 3.1 70B outperformed Llama 3 70B in this area, solving most problems more effectively and showing superior ability to ideify logical traps.

Model recommendations

Lama 3.1 70B

• Best for: Generating long coe, analyzing complex documes, tasks that require extensive text comprehension, advanced logical reasoning, and applications benefit from larger text windows and greater output capacities.
• Not suitable for: Time-sensitive applications that require fast responses, real-time ieractions with minimal latency importa, or projects with limited computing resources that cannot adapt to increased model demand.

Lama 3 70B

• Best for: Applications requiring fast response time, real-time ieractions, efficie coding tasks, shorter docume processing and projects where computing efficiency is a priority.
• Not suitable for: Tasks that involve very long documes or complex text comprehension beyond its 8K text window, advanced logical reasoning problems, or applications that require extensive text information processing.

How best LLM Choose open source?

Self-hosted open source models have their own advaages and offer full corol and customization. However, it may be inconvenie for developers looking for an easier and smoother way to test these models.

Consider using the Keywords AI platform, which allows you to access and test over 200 LLMs using a consiste format. With Keywords AI, you can test all trend models with a simple API call or use the model playground to test them instaly.

conclusion

Choosing between the Lama 3 70B and the Lama 3.1 70B depends on your needs. The Lama 3.1 70B is better suited for complex tasks with more text, while the Lama 3 70B is faster for simpler tasks. Think about what is more importa to your project – speed or power. You can test both models to see which one works best for you.

Keywords AI’s LLM monitoring platform can call over 200 LLMs in OpenAI format using an API key and provide insights io your AI products. With just 2 lines of code, you can build better AI products with full visibility.