AI companions are more than just a passing trend; they could become a $150 billion industry by 2030, according to a recent article by Ark Invest. With the potential to revolutionize how we interact with technology and each other, AI companionship represents the next frontier in digital entertainment.
Companion apps like Replika, Gatebox, HeraHaven, and SoulMachines attract millions of users every month, according to Similarweb data.
But if you’re considering building an AI companion, where do you start? Specifically, which large language model (LLM) should you choose to power your app? Let me walk you through the best open-source LLMs currently available and why they might be the perfect fit for your project.
Choosing the Right LLM for AI Companionship
When thinking about AI companionship, one of the first decisions you’ll need to make is what kind of open-source LLM to use. There are several types of LLMs, but they generally fall into three categories: base models, instruction-tuned models, and chat-tuned models.
Why Chat-Tuned Models Are Essential
Base models are the raw, unrefined versions of LLMs that have been trained on large datasets but lack the fine-tuning required for specific tasks. Instruction-tuned models have been refined to follow human instructions more accurately. However, when it comes to creating AI companions, chat-tuned models are the way to go. These models are specifically optimized for conversational interactions, making them better suited for the nuanced, ongoing dialogues that characterize AI companionship.
Model Size: How Big Is Big Enough?
Another key consideration is the size of the model. For most conversational chatbots, an 8B parameter model should suffice. These models offer a good balance between performance and resource efficiency, making them ideal for most applications. However, if you’re looking to go above and beyond—perhaps aiming to create a more sophisticated AI—you might want to explore models with up to 70B parameters.
The 5 Best Open-Source LLMs for AI Companionship
Here’s a list of some of the best open-source LLMs that are particularly well-suited for creating AI companions:
1. Hermes-3 Llama-3.1-8B
Hermes-3 Llama-3.1-8B is a powerful model that’s been finely tuned for chat applications. It offers a good balance between capability and efficiency, making it a top choice for AI companionship.
2. Yi-1.5-9B-Chat
Yi-1.5-9B-Chat is another excellent option, boasting a slightly larger parameter count, which allows for more complex and nuanced conversations. If your AI companion needs to handle a wide range of topics with ease, this model is worth considering.
3. InternLM2 5-7B Chat
InternLM2 5-7B Chat is a lighter model that still packs a punch. Its smaller size makes it ideal for applications where resources are limited but conversational depth is still a priority.
4. Humanish-Roleplay-Llama-3.1-8B
Humanish-Roleplay-Llama-3.1-8B is designed for roleplay scenarios, making it perfect for users who want an AI companion that can take on different personas. Whether it’s a friendly chat or a more complex interaction, this model excels at maintaining character.
5. OpenChat-3.5-1210
OpenChat-3.5-1210 is one of the larger models on this list and is optimized for deep, engaging conversations. If your AI companion needs to offer an immersive experience, this model is a strong contender.
If you’re interested in seeing how these models stack up against others, you can visit the Open LLM Leaderboard for the most recent comparisons.
Taking Your AI Companion to the Next Level with Fine Tuning
While these models are impressive right out of the box, there’s always room for improvement. With enough prompting, you should be able to get decent results for most applications. However, if you’re looking for a more advanced approach, consider fine-tuning one of these models to better suit your specific needs. Fine-tuning allows you to tweak the model’s behavior, making it more aligned with your desired user experience.
In conclusion, the potential for AI companions is vast, and the right LLM can make all the difference in creating a compelling, engaging experience. Whether you’re building the next million user app or a more niche application, these open-source models provide a strong foundation for success. So, dive in, experiment, and see what you can create with the incredible power of modern LLMs.
Top comments (2)
Interesting model selection. Do you think if you finetuned models for chat at around 3B parameters (Gemma2 / Phi3) will they have enough capabitilies for this kind of application ?
Honestly, I’ve never tried it. It might actually work, given the progress in small models. But since the training and inference costs are roughly the same (both 3B and 8B models can fit on a single 24GB GPU), I’ve always opted for the ~8B ones.