15 Best Large Language Models in September 2024
By Alex • Updated Sep 1, 2024
Since the release of ChatGPT in late 2022, we've witnessed an astonishing pace of development in Large Language Models (LLMs).
Companies like OpenAI, Anthropic, and Google are rapidly releasing updates that offer improved output quality, faster processing speeds, and expanded capabilities.
In this article, we'll explore the top 15 LLMs you should consider today.
Name | Provider | Score ¹ | Context ² | Cutoff ³ | Vision ⁴ | License |
|---|---|---|---|---|---|---|
OpenAI | 1316 | 128K | Oct 2023 | Yes | Proprietary | |
1301 | 2M | Nov 2023 | Yes | Proprietary | ||
xAI | 1295 | 128K | Unknown | Yes | Proprietary | |
OpenAI | 1274 | 128K | Oct 2023 | Yes | Proprietary | |
1271 | 1M | Nov 2023 | Yes | Proprietary | ||
Anthropic | 1270 | 200K | Apr 2024 | Yes | Proprietary | |
Meta | 1266 | 128K | Dec 2023 | No | Open Source | |
xAI | 1265 | 128K | Unknown | Yes | Proprietary | |
OpenAI | 1257 | 128K | Dec 2023 | Yes | Proprietary | |
OpenAI | 1251 | 8K | Apr 2023 | Yes | Proprietary | |
Mistral | 1250 | 128K | Unknown | No | Proprietary | |
Meta | 1248 | 128K | Dec 2023 | No | Open Source | |
Anthropic | 1248 | 200K | Aug 2023 | Yes | Proprietary | |
1218 | 8K | Unknown | No | Open Source | ||
AI21 | 1213 | 256K | Mar 2024 | No | Open Source |
¹ LMSys Chatbot Arena Score, ² Maximum Input Context Length, ³ Training Data Cutoff, ⁴ Image Input
1. GPT-4o (OpenAI)
GPT-4o is OpenAI's latest and most advanced language model, released in May 2024. It represents a significant leap forward in AI capabilities, combining text, audio, and visual processing in a single model.
Key Features
- Multimodal processing: Handles text, audio, and images seamlessly
- Real-time interactions: Responds to audio inputs in as little as 232 milliseconds
- Multilingual support: Proficient in over 50 languages
- Cost-effective: 50% cheaper than GPT-4 Turbo with twice the speed
- Expanded context window: 128,000 tokens, allowing for longer conversations
My Take
I've been impressed with GPT-4o's performance across various tasks. Its ability to process multiple input types simultaneously opens up new possibilities for AI applications.
The real-time audio responses feel remarkably natural, and the improved vision capabilities are a standout feature. While it's not perfect, GPT-4o's advancements in speed, cost, and multilingual support make it a strong contender in the current LLM landscape.
2. Gemini 1.5 Pro (Google)
Gemini 1.5 Pro is Google's latest large language model, released in early 2024. It builds on the success of its predecessor, Gemini 1.0, with significant improvements in performance and capabilities.
Key Features
- Massive context window: Can process up to 2 million tokens, allowing for analysis of lengthy documents, videos, and audio files.
- Multimodal capabilities: Handles text, images, audio, and video inputs seamlessly.
- Mixture-of-Experts architecture: Enables more efficient processing and improved performance.
- Enhanced reasoning: Excels at complex tasks requiring long-context understanding.
- Improved efficiency: Delivers comparable results to Gemini 1.0 Ultra with lower computational overhead.
My Take
I've been impressed with Gemini 1.5 Pro's ability to handle massive amounts of data in a single pass.
The 2 million token context window is a huge leap forward, making it incredibly useful for tasks like document analysis and video comprehension.
In my testing, it's shown remarkable accuracy and speed, often outperforming other top models.
3. Grok-2 (xAI)
Grok-2 is the latest large language model from xAI, Elon Musk's artificial intelligence company. Released in 2024, it builds on the capabilities of its predecessor while introducing new features and performance improvements.
Key Features
- Enhanced reasoning and coding abilities
- Real-time data processing from the X platform
- Image generation capabilities using FLUX.1 service
- Available in two versions: Grok-2 and Grok-2 mini
- Outperforms some leading models in benchmark tests
- Distinctive personality with wit and humor
My Take
I've found Grok-2 to be a strong contender in the LLM space. Its integration with X gives it an edge in accessing current information, while its personality makes interactions more engaging.
Overall, Grok-2 offers a unique blend of capabilities that make it worth considering, especially for those already using the X platform.
4. GPT-4o mini (OpenAI)
GPT-4o mini is OpenAI's latest cost-efficient small language model. It offers impressive capabilities at a fraction of the cost of larger models, making advanced AI more accessible.
Key Features
- Multimodal capabilities: Supports text and image inputs, with future plans for audio and video.
- Large context window: 128,000 tokens, allowing for processing of lengthy texts.
- Improved performance: Scores 82% on the MMLU benchmark, outperforming GPT-3.5 Turbo.
- Cost-effective: Priced at 15 cents per million input tokens and 60 cents per million output tokens.
- Versatility: Suitable for a wide range of tasks, from customer support to content generation.
My Take
I'm impressed by GPT-4o mini's balance of performance and affordability. Its ability to handle complex tasks while remaining cost-effective makes it a strong contender in the AI landscape.
The large context window is particularly useful for processing extensive documents or conversations.
For developers and businesses looking to scale AI applications without breaking the bank, GPT-4o mini is definitely worth considering.
5. Gemini 1.5 Flash (Google)
Gemini 1.5 Flash is Google's latest lightweight AI model, designed for speed and efficiency. It offers impressive capabilities while being cost-effective, making it an attractive option for developers and businesses.
Key Features
- Multimodal capabilities: Supports text, image, audio, and video inputs.
- Long context window: 1 million tokens (2 million via waitlist), allowing for processing of extensive content.
- High-speed performance: Sub-second average first-token latency for most use cases.
- Cost-effective: Priced at $0.35 for input and $0.53 for output per 128K tokens.
- Versatility: Excels in summarization, chat applications, image and video captioning, and data extraction.
My Take
I'm impressed by Gemini 1.5 Flash's balance of performance and affordability. Its multimodal capabilities and extensive context window make it a versatile tool for various applications.
The model's speed and efficiency are particularly noteworthy, potentially making it a go-to choice for high-volume, time-sensitive tasks.
6. Claude 3.5 Sonnet (Anthropic)
Claude 3.5 Sonnet is Anthropic's latest AI model, offering a blend of advanced capabilities and cost-effectiveness. It represents a significant leap forward in AI performance, outpacing many of its competitors in various benchmarks.
Key Features
- Superior intelligence: Excels in graduate-level reasoning, undergraduate knowledge, and coding proficiency.
- Enhanced speed: Operates twice as fast as Claude 3 Opus.
- Improved vision capabilities: Surpasses previous models in visual reasoning tasks.
- Large context window: 200,000 tokens for processing extensive content.
- Cost-effective: Priced at $3 per million input tokens and $15 per million output tokens.
- Artifacts feature: Allows real-time interaction with AI-generated content.
- Multimodal support: Handles text, image, and code inputs effectively.
My Take
Claude 3.5 Sonnet's ability to handle complex tasks with increased speed and accuracy makes it a standout option for both developers and businesses.
The improved vision capabilities and the innovative Artifacts feature are particularly noteworthy, opening up new possibilities for AI-assisted work.
7. Llama 3.1 405B (Meta)
Llama 3.1 405B is Meta's largest open-source language model with 405 billion parameters. It competes with top closed-source models in performance across various tasks.
Key Features
- Context: 128,000 token window
- Multimodal: Handles text, image, and code
- Multilingual: Effective across languages
- Open-source: Customizable and developable
My Take
I'm impressed by Llama 3.1 405B's capabilities, particularly its performance on benchmarks like MMLU and ARC Challenge.
Its open-source nature is a big plus for AI innovation. Overall, it's an important development in open-source AI, and I'm interested to see its applications across different fields.
8. Grok-2 mini (xAI)
Grok-2 mini is xAI's streamlined version of their flagship Grok-2 model, designed for speed and efficiency.
It offers a balance between performance and rapid response times, making it suitable for a wide range of applications.
Key Features
- Speed: Optimized for quick responses
- Real-time data: Access to current information from X platform
- Multimodal: Handles text, image, and code inputs
- Cost-effective: Available to X Premium users
My Take
I'm impressed by Grok-2 mini's ability to deliver quick, accurate responses while maintaining a high level of performance.
Its access to real-time data from X gives it an edge in staying current.
While it may not match the full capabilities of larger models, its balance of speed and efficiency makes it a strong contender for everyday AI tasks.
9. GPT-4 Turbo (OpenAI)
GPT-4 Turbo is OpenAI's enhanced version of their GPT-4 language model.
It offers improved capabilities and performance over its predecessor, maintaining its relevance in the AI landscape despite newer models like GPT-4o.
Key Features
- Large context window: 128,000 tokens
- Multimodal: Processes text, image, and code inputs
- Improved reasoning: Enhanced logical and analytical skills
- Fine-tuning: Customizable for specific use cases
My Take
While OpenAI now has more advanced models like GPT-4o, GPT-4 Turbo still holds its ground with solid performance.
The expanded context window and multimodal processing are particularly useful for complex tasks.
Overall, GPT-4 Turbo remains a strong contender in the AI field, offering a good balance of capabilities and efficiency, even as newer models emerge.
10. GPT-4 (OpenAI)
GPT-4 is OpenAI's fourth-generation large language model, released in March 2023.
While now considered outdated compared to newer models, it still offers impressive capabilities that hold up well in 2024.
Key Features
- Multimodal input: Processes both text and images
- Multilingual proficiency: Performs well across languages
- Fine-tuning options: Customizable for specific use cases
My Take
Despite being over a year old in the fast-moving world of AI, I'm still impressed by GPT-4's performance.
OpenAI has since released more advanced models like GPT-4 Turbo and GPT-4o, which outperform GPT-4 in various aspects.
However, GPT-4's capabilities remain solid for many applications.
11. Mistral Large 2 (Mistral)
Mistral Large 2 is Mistral AI's latest flagship language model, released in July 2024.
It offers significant improvements in various areas, including code generation, mathematics, reasoning, and multilingual support.
Key Features
- Large context window: 128,000 tokens
- Multilingual: Supports dozens of languages, including major European and Asian languages
- Coding proficiency: Handles over 80 programming languages
- Reduced hallucinations: Enhanced accuracy and reliability in outputs
- Function calling: Capable of executing parallel and sequential function calls
My Take
Mistral Large 2 strikes a good balance of performance and efficiency.
While not revolutionary, it's a solid improvement over predecessors.
Its availability on major cloud platforms and flexible licensing options add to its appeal for researchers and businesses alike.
12. Llama 3.1 70B (Meta)
Llama 3.1 70B is one of Meta's latest open-source language model, boasting 70 billion parameters.
Key Features
- Open-source: Freely available for research and commercial use
- Long context window: Supports up to 32,768 tokens
- Multimodal: Handles text, image, and code inputs
- Multilingual: Strong capabilities across multiple languages
My Take
I'm impressed by Llama 3.1 70B's capabilities, especially as an open-source model.
While not matching top-tier models in every aspect, its accessibility and flexibility are significant advantages.
Its efficiency allows for deployment on modest hardware, making it a valuable tool for researchers and developers.
13. Claude 3 Opus (Anthropic)
Claude 3 Opus is Anthropic's flagship large language model, released in March 2024.
While now surpassed by Claude 3.5 Sonnet, it still offers impressive capabilities that hold up well in the rapidly evolving AI landscape.
Key Features
- Multimodal: Processes text, images, and code inputs
- Large context window: 200,000 tokens (1M for specific use cases)
- Multilingual proficiency: Strong performance across languages
- Enhanced accuracy: Reduced hallucinations and improved factual reliability
- Ethical constraints: Built-in safety measures and guidelines
My Take
While not the absolute latest, Claude 3 Opus remains a powerful tool for businesses and researchers who need a reliable, capable AI assistant.
Its performance on benchmarks like MMLU and GPQA showcases its strong reasoning abilities, even as newer models push the boundaries further.
14. Gemma 2 27B (Google)
Gemma 2 27B is Google's latest open-source large language model, released in June 2024.
It offers impressive capabilities while maintaining efficiency, making it a strong contender among larger models.
Key Features
- Open-source: Freely available for research and commercial use
- Long context: Supports up to 8,192 tokens
- Multimodal: Handles text, image, and code inputs
- Safety-focused: Built-in ethical constraints and guidelines
My Take
The focus on efficiency and single-device deployment enhances Gemma 2’s accessibility.
While not topping every benchmark, its balance of capability, efficiency, and open-source nature is valuable.
15. Jamba 1.5 Large (AI21)
Jamba 1.5 Large is AI21's latest flagship language model, released in August 2024.
It features a hybrid architecture combining Transformer and Mamba technologies, offering a unique balance of performance and efficiency.
Key Features
- Hybrid architecture: Mixture of Experts (MoE) model with 398B total parameters (94B active)
- Multilingual: Supports multiple languages including English, Spanish, French, and Arabic
- Efficient inference: Up to 2.5x faster than comparable models for long contexts
- Open model: Available under a permissive license for research and commercial use
My Take
The combination of Transformer and Mamba technologies offers a good balance of performance and efficiency, especially for long-context tasks.
Frequently Asked Questions
What are Large Language Models (LLMs)?
LLMs are powerful AI systems that can be used for a wide range of tasks involving text generation and understanding.
They're trained on massive datasets to learn patterns in language.
The same core LLM can often be applied to dozens of different use cases like chatbots, summarization, translation, code generation, and more - just by changing how it's prompted.
How do LLMs work?
LLMs process text using word embeddings to capture meaning and relationships between words.
A transformer model then uses an encoder to understand context and a decoder to generate human-like text based on the input.
During training, the model predicts the next word in sequences and adjusts its parameters to improve, essentially teaching itself through vast amounts of examples.
What are some key parameters that affect LLM performance?
Important parameters include the model architecture (like transformers), model size (number of parameters), quality and volume of training data, and hyperparameters that control the learning process.
Larger models with more parameters can handle more complex tasks but require more computational resources.
What is fine-tuning for LLMs?
Fine-tuning involves taking a pre-trained LLM and further training it on a smaller, task-specific dataset.
This allows the model to adapt its general language knowledge to perform better on particular applications. Fine-tuning is faster and requires less data than training from scratch.
Conclusion
The world of Large Language Models is evolving rapidly.
Each new release pushes the boundaries of what's possible - from GPT-4o's high output quality to Gemini 1.5 Pro's massive context window.
What's more, the rise of efficient models like Grok-2 mini and GPT-4o mini is making advanced AI more accessible, allowing developers and businesses to harness the power of these technologies without breaking the bank.