I receive similar questions almost every day. After helping to build over 20 AI entities and investing considerable resources into testing models, I have summarized some truly effective experiences.
Here is a complete guide on how to choose the right LLM.
Image source: TechFlow Deep Tide
The current large language model (LLM) industry is changing rapidly. Almost every week, new models are released, each claiming to be the 'best'.
But the reality is: no single model can meet all needs.
Each model has its specific applicable scenarios.
I have tested dozens of models, hoping to help you avoid unnecessary time and money waste through my experience.
Image source: TechFlow Deep Tide
It should be noted: this article is not based on laboratory benchmarks or marketing promotions.
What I will share is based on the practical experience of building AI entities and generative AI (GenAI) products over the past two years.
First, we need to understand what LLMs are:
Large language models (LLMs) are like teaching computers to 'speak human language'. They predict the next most likely word based on the input you provide.
The starting point of this technology is this classic paper: Attention Is All You Need
Basic knowledge - Closed source code vs. open source code LLMs:
Closed source code: For example, GPT-4 and Claude, usually pay-per-use and hosted by the provider.
Open source code: For example, Meta's Llama and Mixtral, require users to deploy and run themselves.
When first encountering these terms, you may feel confused, but it is essential to understand the differences between the two.
Image source: TechFlow Deep Tide
Model size does not equate to better performance:
For example, 7B indicates that the model has 7 billion parameters.
But larger models do not always perform better. The key is to choose a model that suits your specific needs.
Image source: TechFlow Deep Tide
If you need to build X/Twitter bots or social AI:
@xai's Grok is a very good choice:
Offers a generous free quota
Excellent understanding of social context
Although it is closed source, it is definitely worth trying
Highly recommend this model for beginner developers! (Rumor has it:
@ai16zdao's Eliza default model is using XAI Grok)
If you need to handle multilingual content:
@Alibaba_Qwen's QwQ model performed exceptionally well in our tests, especially in Asian language processing.
It should be noted that the training data for this model primarily comes from mainland China, so some content may be missing information.
Image source: TechFlow Deep Tide
If you need a general-purpose model or one with strong reasoning abilities:
@OpenAI's model remains a leader in the industry:
Performance is stable and reliable
After extensive real-world testing
Has strong security mechanisms
This is the ideal starting point for most projects.
Image source: TechFlow Deep Tide
If you are a developer or content creator:
@AnthropicAI's Claude is my main tool for daily use:
Coding abilities are quite impressive
Responses are clear and detailed
Very suitable for handling creative-related work
Image source: TechFlow Deep Tide
Meta's Llama 3.3 has recently attracted a lot of attention:
Performance is stable and reliable
Open source models, flexible and free
Can be trialed through @OpenRouterAI or @GroqInc
For example, crypto x AI projects like @virtuals_io are developing products based on it.
Image source: TechFlow Deep Tide
If you need role-playing AI:
@TheBlokeAI's MythoMax 13B is currently a leader in the role-playing industry, ranking high in related charts for several consecutive months.
Cohere's Command R+ is an underrated excellent model:
Performs excellently in role-playing tasks
Capable of easily handling complex tasks
Supports a context window of up to 128,000, with a longer 'memory capacity'
Image source: TechFlow Deep Tide
Google's Gemma model is a lightweight but powerful choice:
Focus on specific tasks, performing excellently
Budget-friendly
Suitable for cost-sensitive projects
Personal experience: I often use the small Gemma model as an 'unbiased referee' in the AI process, and it performs exceptionally well in validation tasks!
Image source: TechFlow Deep Tide
Gemma
Models from @MistralAI are worth mentioning:
Open source but with high-end quality
The Mixtral model performs very strongly
Especially good at complex reasoning tasks
It has received wide acclaim from the community and is definitely worth a try.
The cutting-edge AI in your hands.
Professional advice: Try mixing and matching!
Different models each have their advantages
Can create AI 'teams' for complex tasks
Let each model focus on what it does best
It's like building a dream team, with each member having a unique role and contribution.
How to get started quickly:
Use @OpenRouterAI or @redpill_gpt for model testing; these platforms support cryptocurrency payments, which is very convenient
Is an excellent tool for comparing the performance of different models
If you want to save costs and run models locally, you can try using @ollama to experiment with your own GPU.
Image source: TechFlow Deep Tide
If you pursue speed, @GroqInc's LPU technology offers extremely fast inference speed:
Although the choice of models is limited
It performs very well for deployment in production environments
Image source: TechFlow Deep Tide
[Disclaimer] The market has risks, and investments should be cautious. This article does not constitute investment advice, and users should consider whether any opinions, views, or conclusions in this article align with their specific circumstances. Invest at your own risk.
This article is reproduced with permission from: (Deep Tide TechFlow)
Original author: superoo7
'Want to create your own AI Agent? 12 LLM models to collect, you can also train good tools!' This article was first published in 'Crypto City'
