
Best LLMs For Sentiment Analysis: Overview, Tables and Costs
Hey there! I've been diving deep into the world of Language Models lately, specifically looking at how they handle sentiment analysis. While I haven't personally tested all these models (that would be quite the undertaking!), I've gathered data from various sources to give you a comprehensive overview of what's available right now.
What are the best LLMs for Sentiment Analysis?
When it comes to analyzing sentiment in text, not all LLMs are created equal. Some excel at understanding nuanced emotions, while others are great for processing large volumes of text quickly. I've selected five standout models that offer different advantages depending on your needs.
Model | Context Window | Price (Input/Output) | Best For |
---|---|---|---|
Claude-3-Haiku | 200K tokens | $0.25/$1.25 per 1M | High-volume, budget-conscious analysis |
Gemini-1.5-Pro | 2M tokens | $1.25/$5 per 1M | Large-scale document analysis |
Command-R | 128K tokens | $0.15/$0.6 per 1M | Consistent classification tasks |
Mistral-Large-Latest | 128K tokens | $3/$9 per 1M | High-accuracy requirements |
GPT-4O-Mini | 128K tokens | $0.15/$0.6 per 1M | Balanced performance |

Anthropic - Claude-3-Haiku
If you're looking to analyze sentiment in large volumes of text without breaking the bank, Claude-3-Haiku is your friend. It's Anthropic's most affordable option, but don't let that fool you – it still packs a punch when it comes to understanding text sentiment.
Context Window | 200K tokens |
Price (Input) | $0.25 per 1M tokens |
Price (Output) | $1.25 per 1M tokens |

Google - Gemini-1.5-Pro
When you need to analyze sentiment across entire documents or datasets, Gemini-1.5-Pro shines with its massive context window. It's like having a research assistant who can read and understand an entire book in one go!
Context Window | 2M tokens |
Price (Input) | $1.25 per 1M tokens |
Price (Output) | $5 per 1M tokens |

Cohere - Command-R
Command-R is like that reliable friend who always gives you consistent advice. It's particularly good at classification tasks, making it perfect for straightforward sentiment analysis projects.
Context Window | 128K tokens |
Price (Input) | $0.15 per 1M tokens |
Price (Output) | $0.6 per 1M tokens |

Mistral - Mistral-Large-Latest
When accuracy is your top priority and you're willing to invest a bit more, Mistral-Large-Latest is your go-to option. It's like having a sentiment analysis expert on your team.
Context Window | 128K tokens |
Price (Input) | $3 per 1M tokens |
Price (Output) | $9 per 1M tokens |

OpenAI - GPT-4O-Mini
Think of GPT-4O-Mini as the jack-of-all-trades in the sentiment analysis world. It offers a great balance of features at a reasonable price point, making it a solid choice for most projects.
Context Window | 128K tokens |
Price (Input) | $0.15 per 1M tokens |
Price (Output) | $0.6 per 1M tokens |
Remember, choosing the right LLM for sentiment analysis isn't just about picking the most powerful or the cheapest option. It's about finding the right balance for your specific needs. Consider factors like your budget, the volume of text you need to analyze, and how accurate you need the results to be.
If you're just starting out, I'd recommend trying GPT-4O-Mini or Claude-3-Haiku first – they offer great value for money and are capable enough for most sentiment analysis tasks. For enterprise-level needs, you might want to look at Gemini-1.5-Pro or Mistral-Large-Latest. And if you're doing a lot of straightforward classification work, Command-R could be your best bet.