Top 6 Monoliths: Mammoth Data Models Highlighted

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Key Takeaways

• OpenAI’s GPT-4 is the most advanced and widely used large language model, with 1.76 trillion parameters and multimodal abilities.
• Anthropic’s Claude 2 competes with GPT-4 in creative writing tasks and holds its own despite having fewer resources.
• Google’s PaLM 2, while not a GPT-4 killer, is a powerful language model with strong multilingual and creative abilities. Falcon-180B is an open-source model that rivals commercial giants and can stand toe-to-toe with GPT-3.5.

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It’s AI season, and tech companies are churning out large language models like bread from a bakery. New models are released rapidly, and it’s becoming too hard to keep track.

But amidst the flurry of new releases, only a few models have risen to the top and proven themselves as true contenders in the large language model space. As we approach the end of 2023, we’ve put together the six most impressive large language models you should try.

1. OpenAI’s GPT-4

GPT-4 is the most advanced publicly available large language model to date. Developed by OpenAI and released in March 2023, GPT-4 is the latest iteration in the Generative Pre-trained Transformer series that began in 2018. With its immense capabilities, GPT-4 has become one of the most widely used and most popular large language models in the world.

While not officially confirmed, sources estimate GPT-4 may contain a staggering 1.76 trillion parameters, around ten times more than its predecessor, GPT-3.5, and five times larger than Google’s flagship, PaLM 2. This massive scale enables GPT-4’s multimodal abilities, allowing it to process both text and images as input. As a result, GPT-4 can interpret and describe visual information like diagrams and screenshots in addition to text. Its multimodal nature provides a more human-like understanding of real-world data.

In scientific benchmarks, GPT-4 significantly outperforms other contemporary models across various tests. While benchmarks alone don’t fully demonstrate a model’s strengths, real-world use cases have shown that GPT-4 is exceptionally adept at solving practical problems intuitively. GPT-4 is currently billed at $20 per month and accessible through ChatGPT’s Plus plan .

2. Anthropic’s Claude 2

Image Credit: Anthropic

While not as popular as GPT-4, Claude 2, developed by Anthropic AI, can match GPT -4’s technical benchmarks and real-world performance in several areas. In some standardized tests, including select exams, Claude 2 outperforms GPT-4. The AI language model also has a vastly superior context window at around 100,000 tokens, compared to GPT -4’s 8k and 32k tokens models. Although larger context length doesn’t always translate to better performance, Claude 2’s expanded capacity provides clear advantages, like digesting entire 75,000-word books for analysis.

In overall performance, GPT-4 remains superior, but our in-house testing shows Claude 2 exceeds it in several creative writing tasks. Claude 2 also trails GPT-4 in programming and math skills based on our evaluations but excels at providing human-like, creative answers. When we prompted all the models on this list to write or rewrite a creative piece, six times out of ten, we chose Claude 2’s result for its natural-sounding human-like results. Currently, Claude 2 is available for free through the Claude AI chatbot . There’s also a $20 paid plan for access to extra features.

Despite having less financial backing than giants like OpenAI and Microsoft, Anthropic’s Claude 2 AI model holds its own against the popular GPT models and Google’s PaLM series. For an AI with fewer resources, Claude 2 is impressively competitive. If forced to bet on which existing model has the best chance of rivaling GPT in the near future, Claude 2 seems the safest wager. Though outgunned in funding, Claude 2’s advanced capabilities suggest it can go toe-to-toe with even well-funded behemoths (though it’s worth noting that Google has made several large contributions to Anthropic). The model punches above its weight class and shows promise as an emerging challenger.

3. OpenAI’s GPT-3.5

Image Credit: Marcelo Mollaretti/Shutterstock

While overshadowed by the release of GPT-4, GPT-3.5 and its 175 billion parameters should not be underestimated. Through iterative fine-tuning and upgrades focused on performance, accuracy, and safety, GPT-3.5 has come a long way from the original GPT-3 model. Although it lacks GPT -4’s multimodal capabilities and lags behind in context length and parameter count, GPT-3.5 remains highly capable, with GPT-4 being the only model able to surpass its all-around performance decisively.

Despite being a second-tier model in the GPT family, GPT-3.5 can hold its own and even outperform Google and Meta’s flagship models on several benchmarks. In side-by-side tests of mathematical and programming skills against Google’s PaLM 2, the differences were not stark, with GPT-3.5 even having a slight edge in some cases. More creative tasks like humor and narrative writing saw GPT-3.5 pull ahead decisively.

So, while GPT-4 marks a new milestone in AI, GPT-3.5 remains an impressively powerful model, able to compete with and sometimes surpass even the most advanced alternatives. Its continued refinement ensures it stays relevant even alongside flashier next-gen models.

4. Google’s PaLM 2

Image Credit: Google

When evaluating an AI model’s capabilities, the proven formula is to read the technical report and check benchmark scores, but take everything you learned with a grain of salt and test the model yourself. Counterintuitive as it may seem, benchmark results don’t always align with real-world performance for some AI models. On paper, Google’s PaLM 2 was supposed to be the GPT-4 killer, with official test results suggesting it matches GPT-4 across some benchmarks. However, in day-to-day use, a different picture emerges.

In logical reasoning, mathematics, and creativity, PaLM 2 falls short of GPT-4. It also lags behind Anthropic’s Claude in a range of creative writing tasks. However, although it fails to live up to its billing as a GPT-4 killer, Google’s PaLM 2 remains a powerful language model in its own right, with immense capabilities. Much of the negative sentiment around it stems from comparisons to models like GPT-4 rather than outright poor performance.

With 340 billion parameters, PaLM 2 stands among the world’s largest models. It particularly excels at multilingual tasks and possesses strong math and programming abilities. Although not the best at it, PaLM 2 is also quite efficient at creative tasks like writing. So, while benchmarks painted an optimistic picture that didn’t fully materialize, PaLM 2 still demonstrates impressive AI skills, even if not surpassing all competitors across the board.

5. TII’s Falcon-180B

Unless you’ve been keeping up with the rapid pace of AI language model releases, you have likely never encountered Falcon-180B. Developed by UAE’s Technology Innovation Institute, the 180 billion parameter Falcon-180 is one of the most powerful open-source language models out there, even if it lacks the name recognition of GPT models or the widespread use of Meta’s Llama 2. But make no mistake - Falcon-180B can stand toe-to-toe with the best in class.

Benchmark results reveal that Falcon-180B outperforms most open-source models and competes with commercial juggernauts like PaLM 2 and GPT-3.5. In testing math, coding, reasoning, and creative writing tasks, it even edged out GPT-3.5 and PaLM 2 at times. If ranking GPT-4, GPT-3.5, and Falcon-180B, we’d place Falcon-180B squarely between GPT-4 and GPT-3.5 for its strengths in several use cases.

While we can’t confidently say it is better than GPT-3.5 in overall performance, it makes a case for itself. While obscure, this model deserves attention for matching or exceeding the capabilities of better-known alternatives. You can try out the Falcon-180B model on Hugging Face (an open-source LLM platform).

6. Meta AI’s Llama 2

Llama 2, Meta AI’s 70 billion parameter large language model, builds on its predecessor, Llama 1. While smaller than leading models, Llama 2 significantly outperforms most publicly available open-source LLMs in benchmarks and real-world use. An exception would be the Falcon-180B.

We tested Llama 2 against GPT-4, GPT-3.5, Claude 2, and PaLM 2 to gauge its capabilities. Unsurprisingly, GPT-4 outclassed Llama 2 across nearly all parameters. However, Llama 2 held its own against GPT-3.5 and PaLM 2 in several evaluations. While it would be inaccurate to claim Llama 2 is superior to PaLM 2, Llama 2 solved many problems that stumped PaLM 2, including coding tasks. Claude 2 and GPT-3.5 edged out Llama 2 in some areas but were only decisively better in a limited number of tasks.

So, while not exceeding the capabilities of the largest proprietary models, open-source Llama 2 punches above its weight class . For an openly available model, it demonstrates impressive performance, rivaling AI giants like PaLM 2 in select evaluations. Llama 2 provides a glimpse of the future potential of open-source language models.

The Performance Gap Between AI Models Is Narrowing

Although the AI landscape is evolving at a blistering pace, OpenAI’s GPT-4 remains the leader of the pack. However, while GPT-4 remains unmatched in scale and performance, models like Claude 2 show that with enough skill, smaller models can compete in select areas. Google’s PaLM 2, despite falling short of some lofty expectations, still exhibits profound capabilities. And Falcon-180B proves that open-source initiatives can stand shoulder-to-shoulder with industry titans given sufficient resources.

MUO VIDEO OF THE DAY

SCROLL TO CONTINUE WITH CONTENT

It’s AI season, and tech companies are churning out large language models like bread from a bakery. New models are released rapidly, and it’s becoming too hard to keep track.

But amidst the flurry of new releases, only a few models have risen to the top and proven themselves as true contenders in the large language model space. As we approach the end of 2023, we’ve put together the six most impressive large language models you should try.

1. OpenAI’s GPT-4

GPT-4 is the most advanced publicly available large language model to date. Developed by OpenAI and released in March 2023, GPT-4 is the latest iteration in the Generative Pre-trained Transformer series that began in 2018. With its immense capabilities, GPT-4 has become one of the most widely used and most popular large language models in the world.

While not officially confirmed, sources estimate GPT-4 may contain a staggering 1.76 trillion parameters, around ten times more than its predecessor, GPT-3.5, and five times larger than Google’s flagship, PaLM 2. This massive scale enables GPT-4’s multimodal abilities, allowing it to process both text and images as input. As a result, GPT-4 can interpret and describe visual information like diagrams and screenshots in addition to text. Its multimodal nature provides a more human-like understanding of real-world data.

In scientific benchmarks, GPT-4 significantly outperforms other contemporary models across various tests. While benchmarks alone don’t fully demonstrate a model’s strengths, real-world use cases have shown that GPT-4 is exceptionally adept at solving practical problems intuitively. GPT-4 is currently billed at $20 per month and accessible through ChatGPT’s Plus plan .

2. Anthropic’s Claude 2

Image Credit: Anthropic

While not as popular as GPT-4, Claude 2, developed by Anthropic AI, can match GPT -4’s technical benchmarks and real-world performance in several areas. In some standardized tests, including select exams, Claude 2 outperforms GPT-4. The AI language model also has a vastly superior context window at around 100,000 tokens, compared to GPT -4’s 8k and 32k tokens models. Although larger context length doesn’t always translate to better performance, Claude 2’s expanded capacity provides clear advantages, like digesting entire 75,000-word books for analysis.

In overall performance, GPT-4 remains superior, but our in-house testing shows Claude 2 exceeds it in several creative writing tasks. Claude 2 also trails GPT-4 in programming and math skills based on our evaluations but excels at providing human-like, creative answers. When we prompted all the models on this list to write or rewrite a creative piece, six times out of ten, we chose Claude 2’s result for its natural-sounding human-like results. Currently, Claude 2 is available for free through the Claude AI chatbot . There’s also a $20 paid plan for access to extra features.

Despite having less financial backing than giants like OpenAI and Microsoft, Anthropic’s Claude 2 AI model holds its own against the popular GPT models and Google’s PaLM series. For an AI with fewer resources, Claude 2 is impressively competitive. If forced to bet on which existing model has the best chance of rivaling GPT in the near future, Claude 2 seems the safest wager. Though outgunned in funding, Claude 2’s advanced capabilities suggest it can go toe-to-toe with even well-funded behemoths (though it’s worth noting that Google has made several large contributions to Anthropic). The model punches above its weight class and shows promise as an emerging challenger.

3. OpenAI’s GPT-3.5

Image Credit: Marcelo Mollaretti/Shutterstock

While overshadowed by the release of GPT-4, GPT-3.5 and its 175 billion parameters should not be underestimated. Through iterative fine-tuning and upgrades focused on performance, accuracy, and safety, GPT-3.5 has come a long way from the original GPT-3 model. Although it lacks GPT -4’s multimodal capabilities and lags behind in context length and parameter count, GPT-3.5 remains highly capable, with GPT-4 being the only model able to surpass its all-around performance decisively.

Despite being a second-tier model in the GPT family, GPT-3.5 can hold its own and even outperform Google and Meta’s flagship models on several benchmarks. In side-by-side tests of mathematical and programming skills against Google’s PaLM 2, the differences were not stark, with GPT-3.5 even having a slight edge in some cases. More creative tasks like humor and narrative writing saw GPT-3.5 pull ahead decisively.

So, while GPT-4 marks a new milestone in AI, GPT-3.5 remains an impressively powerful model, able to compete with and sometimes surpass even the most advanced alternatives. Its continued refinement ensures it stays relevant even alongside flashier next-gen models.

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4. Google’s PaLM 2

Image Credit: Google

When evaluating an AI model’s capabilities, the proven formula is to read the technical report and check benchmark scores, but take everything you learned with a grain of salt and test the model yourself. Counterintuitive as it may seem, benchmark results don’t always align with real-world performance for some AI models. On paper, Google’s PaLM 2 was supposed to be the GPT-4 killer, with official test results suggesting it matches GPT-4 across some benchmarks. However, in day-to-day use, a different picture emerges.

In logical reasoning, mathematics, and creativity, PaLM 2 falls short of GPT-4. It also lags behind Anthropic’s Claude in a range of creative writing tasks. However, although it fails to live up to its billing as a GPT-4 killer, Google’s PaLM 2 remains a powerful language model in its own right, with immense capabilities. Much of the negative sentiment around it stems from comparisons to models like GPT-4 rather than outright poor performance.

With 340 billion parameters, PaLM 2 stands among the world’s largest models. It particularly excels at multilingual tasks and possesses strong math and programming abilities. Although not the best at it, PaLM 2 is also quite efficient at creative tasks like writing. So, while benchmarks painted an optimistic picture that didn’t fully materialize, PaLM 2 still demonstrates impressive AI skills, even if not surpassing all competitors across the board.

5. TII’s Falcon-180B

Unless you’ve been keeping up with the rapid pace of AI language model releases, you have likely never encountered Falcon-180B. Developed by UAE’s Technology Innovation Institute, the 180 billion parameter Falcon-180 is one of the most powerful open-source language models out there, even if it lacks the name recognition of GPT models or the widespread use of Meta’s Llama 2. But make no mistake - Falcon-180B can stand toe-to-toe with the best in class.

Benchmark results reveal that Falcon-180B outperforms most open-source models and competes with commercial juggernauts like PaLM 2 and GPT-3.5. In testing math, coding, reasoning, and creative writing tasks, it even edged out GPT-3.5 and PaLM 2 at times. If ranking GPT-4, GPT-3.5, and Falcon-180B, we’d place Falcon-180B squarely between GPT-4 and GPT-3.5 for its strengths in several use cases.

While we can’t confidently say it is better than GPT-3.5 in overall performance, it makes a case for itself. While obscure, this model deserves attention for matching or exceeding the capabilities of better-known alternatives. You can try out the Falcon-180B model on Hugging Face (an open-source LLM platform).

6. Meta AI’s Llama 2

Llama 2, Meta AI’s 70 billion parameter large language model, builds on its predecessor, Llama 1. While smaller than leading models, Llama 2 significantly outperforms most publicly available open-source LLMs in benchmarks and real-world use. An exception would be the Falcon-180B.

We tested Llama 2 against GPT-4, GPT-3.5, Claude 2, and PaLM 2 to gauge its capabilities. Unsurprisingly, GPT-4 outclassed Llama 2 across nearly all parameters. However, Llama 2 held its own against GPT-3.5 and PaLM 2 in several evaluations. While it would be inaccurate to claim Llama 2 is superior to PaLM 2, Llama 2 solved many problems that stumped PaLM 2, including coding tasks. Claude 2 and GPT-3.5 edged out Llama 2 in some areas but were only decisively better in a limited number of tasks.

So, while not exceeding the capabilities of the largest proprietary models, open-source Llama 2 punches above its weight class . For an openly available model, it demonstrates impressive performance, rivaling AI giants like PaLM 2 in select evaluations. Llama 2 provides a glimpse of the future potential of open-source language models.

The Performance Gap Between AI Models Is Narrowing

Although the AI landscape is evolving at a blistering pace, OpenAI’s GPT-4 remains the leader of the pack. However, while GPT-4 remains unmatched in scale and performance, models like Claude 2 show that with enough skill, smaller models can compete in select areas. Google’s PaLM 2, despite falling short of some lofty expectations, still exhibits profound capabilities. And Falcon-180B proves that open-source initiatives can stand shoulder-to-shoulder with industry titans given sufficient resources.

MUO VIDEO OF THE DAY

SCROLL TO CONTINUE WITH CONTENT

It’s AI season, and tech companies are churning out large language models like bread from a bakery. New models are released rapidly, and it’s becoming too hard to keep track.

But amidst the flurry of new releases, only a few models have risen to the top and proven themselves as true contenders in the large language model space. As we approach the end of 2023, we’ve put together the six most impressive large language models you should try.

1. OpenAI’s GPT-4

GPT-4 is the most advanced publicly available large language model to date. Developed by OpenAI and released in March 2023, GPT-4 is the latest iteration in the Generative Pre-trained Transformer series that began in 2018. With its immense capabilities, GPT-4 has become one of the most widely used and most popular large language models in the world.

While not officially confirmed, sources estimate GPT-4 may contain a staggering 1.76 trillion parameters, around ten times more than its predecessor, GPT-3.5, and five times larger than Google’s flagship, PaLM 2. This massive scale enables GPT-4’s multimodal abilities, allowing it to process both text and images as input. As a result, GPT-4 can interpret and describe visual information like diagrams and screenshots in addition to text. Its multimodal nature provides a more human-like understanding of real-world data.

In scientific benchmarks, GPT-4 significantly outperforms other contemporary models across various tests. While benchmarks alone don’t fully demonstrate a model’s strengths, real-world use cases have shown that GPT-4 is exceptionally adept at solving practical problems intuitively. GPT-4 is currently billed at $20 per month and accessible through ChatGPT’s Plus plan .

2. Anthropic’s Claude 2

Image Credit: Anthropic

While not as popular as GPT-4, Claude 2, developed by Anthropic AI, can match GPT -4’s technical benchmarks and real-world performance in several areas. In some standardized tests, including select exams, Claude 2 outperforms GPT-4. The AI language model also has a vastly superior context window at around 100,000 tokens, compared to GPT -4’s 8k and 32k tokens models. Although larger context length doesn’t always translate to better performance, Claude 2’s expanded capacity provides clear advantages, like digesting entire 75,000-word books for analysis.

In overall performance, GPT-4 remains superior, but our in-house testing shows Claude 2 exceeds it in several creative writing tasks. Claude 2 also trails GPT-4 in programming and math skills based on our evaluations but excels at providing human-like, creative answers. When we prompted all the models on this list to write or rewrite a creative piece, six times out of ten, we chose Claude 2’s result for its natural-sounding human-like results. Currently, Claude 2 is available for free through the Claude AI chatbot . There’s also a $20 paid plan for access to extra features.

Despite having less financial backing than giants like OpenAI and Microsoft, Anthropic’s Claude 2 AI model holds its own against the popular GPT models and Google’s PaLM series. For an AI with fewer resources, Claude 2 is impressively competitive. If forced to bet on which existing model has the best chance of rivaling GPT in the near future, Claude 2 seems the safest wager. Though outgunned in funding, Claude 2’s advanced capabilities suggest it can go toe-to-toe with even well-funded behemoths (though it’s worth noting that Google has made several large contributions to Anthropic). The model punches above its weight class and shows promise as an emerging challenger.

3. OpenAI’s GPT-3.5

Image Credit: Marcelo Mollaretti/Shutterstock

While overshadowed by the release of GPT-4, GPT-3.5 and its 175 billion parameters should not be underestimated. Through iterative fine-tuning and upgrades focused on performance, accuracy, and safety, GPT-3.5 has come a long way from the original GPT-3 model. Although it lacks GPT -4’s multimodal capabilities and lags behind in context length and parameter count, GPT-3.5 remains highly capable, with GPT-4 being the only model able to surpass its all-around performance decisively.

Despite being a second-tier model in the GPT family, GPT-3.5 can hold its own and even outperform Google and Meta’s flagship models on several benchmarks. In side-by-side tests of mathematical and programming skills against Google’s PaLM 2, the differences were not stark, with GPT-3.5 even having a slight edge in some cases. More creative tasks like humor and narrative writing saw GPT-3.5 pull ahead decisively.

So, while GPT-4 marks a new milestone in AI, GPT-3.5 remains an impressively powerful model, able to compete with and sometimes surpass even the most advanced alternatives. Its continued refinement ensures it stays relevant even alongside flashier next-gen models.

4. Google’s PaLM 2

Image Credit: Google

When evaluating an AI model’s capabilities, the proven formula is to read the technical report and check benchmark scores, but take everything you learned with a grain of salt and test the model yourself. Counterintuitive as it may seem, benchmark results don’t always align with real-world performance for some AI models. On paper, Google’s PaLM 2 was supposed to be the GPT-4 killer, with official test results suggesting it matches GPT-4 across some benchmarks. However, in day-to-day use, a different picture emerges.

In logical reasoning, mathematics, and creativity, PaLM 2 falls short of GPT-4. It also lags behind Anthropic’s Claude in a range of creative writing tasks. However, although it fails to live up to its billing as a GPT-4 killer, Google’s PaLM 2 remains a powerful language model in its own right, with immense capabilities. Much of the negative sentiment around it stems from comparisons to models like GPT-4 rather than outright poor performance.

With 340 billion parameters, PaLM 2 stands among the world’s largest models. It particularly excels at multilingual tasks and possesses strong math and programming abilities. Although not the best at it, PaLM 2 is also quite efficient at creative tasks like writing. So, while benchmarks painted an optimistic picture that didn’t fully materialize, PaLM 2 still demonstrates impressive AI skills, even if not surpassing all competitors across the board.

5. TII’s Falcon-180B

Unless you’ve been keeping up with the rapid pace of AI language model releases, you have likely never encountered Falcon-180B. Developed by UAE’s Technology Innovation Institute, the 180 billion parameter Falcon-180 is one of the most powerful open-source language models out there, even if it lacks the name recognition of GPT models or the widespread use of Meta’s Llama 2. But make no mistake - Falcon-180B can stand toe-to-toe with the best in class.

Benchmark results reveal that Falcon-180B outperforms most open-source models and competes with commercial juggernauts like PaLM 2 and GPT-3.5. In testing math, coding, reasoning, and creative writing tasks, it even edged out GPT-3.5 and PaLM 2 at times. If ranking GPT-4, GPT-3.5, and Falcon-180B, we’d place Falcon-180B squarely between GPT-4 and GPT-3.5 for its strengths in several use cases.

While we can’t confidently say it is better than GPT-3.5 in overall performance, it makes a case for itself. While obscure, this model deserves attention for matching or exceeding the capabilities of better-known alternatives. You can try out the Falcon-180B model on Hugging Face (an open-source LLM platform).

6. Meta AI’s Llama 2

Llama 2, Meta AI’s 70 billion parameter large language model, builds on its predecessor, Llama 1. While smaller than leading models, Llama 2 significantly outperforms most publicly available open-source LLMs in benchmarks and real-world use. An exception would be the Falcon-180B.

We tested Llama 2 against GPT-4, GPT-3.5, Claude 2, and PaLM 2 to gauge its capabilities. Unsurprisingly, GPT-4 outclassed Llama 2 across nearly all parameters. However, Llama 2 held its own against GPT-3.5 and PaLM 2 in several evaluations. While it would be inaccurate to claim Llama 2 is superior to PaLM 2, Llama 2 solved many problems that stumped PaLM 2, including coding tasks. Claude 2 and GPT-3.5 edged out Llama 2 in some areas but were only decisively better in a limited number of tasks.

So, while not exceeding the capabilities of the largest proprietary models, open-source Llama 2 punches above its weight class . For an openly available model, it demonstrates impressive performance, rivaling AI giants like PaLM 2 in select evaluations. Llama 2 provides a glimpse of the future potential of open-source language models.

The Performance Gap Between AI Models Is Narrowing

Although the AI landscape is evolving at a blistering pace, OpenAI’s GPT-4 remains the leader of the pack. However, while GPT-4 remains unmatched in scale and performance, models like Claude 2 show that with enough skill, smaller models can compete in select areas. Google’s PaLM 2, despite falling short of some lofty expectations, still exhibits profound capabilities. And Falcon-180B proves that open-source initiatives can stand shoulder-to-shoulder with industry titans given sufficient resources.

MUO VIDEO OF THE DAY

SCROLL TO CONTINUE WITH CONTENT

It’s AI season, and tech companies are churning out large language models like bread from a bakery. New models are released rapidly, and it’s becoming too hard to keep track.

But amidst the flurry of new releases, only a few models have risen to the top and proven themselves as true contenders in the large language model space. As we approach the end of 2023, we’ve put together the six most impressive large language models you should try.

1. OpenAI’s GPT-4

GPT-4 is the most advanced publicly available large language model to date. Developed by OpenAI and released in March 2023, GPT-4 is the latest iteration in the Generative Pre-trained Transformer series that began in 2018. With its immense capabilities, GPT-4 has become one of the most widely used and most popular large language models in the world.

While not officially confirmed, sources estimate GPT-4 may contain a staggering 1.76 trillion parameters, around ten times more than its predecessor, GPT-3.5, and five times larger than Google’s flagship, PaLM 2. This massive scale enables GPT-4’s multimodal abilities, allowing it to process both text and images as input. As a result, GPT-4 can interpret and describe visual information like diagrams and screenshots in addition to text. Its multimodal nature provides a more human-like understanding of real-world data.

In scientific benchmarks, GPT-4 significantly outperforms other contemporary models across various tests. While benchmarks alone don’t fully demonstrate a model’s strengths, real-world use cases have shown that GPT-4 is exceptionally adept at solving practical problems intuitively. GPT-4 is currently billed at $20 per month and accessible through ChatGPT’s Plus plan .

2. Anthropic’s Claude 2

Image Credit: Anthropic

While not as popular as GPT-4, Claude 2, developed by Anthropic AI, can match GPT -4’s technical benchmarks and real-world performance in several areas. In some standardized tests, including select exams, Claude 2 outperforms GPT-4. The AI language model also has a vastly superior context window at around 100,000 tokens, compared to GPT -4’s 8k and 32k tokens models. Although larger context length doesn’t always translate to better performance, Claude 2’s expanded capacity provides clear advantages, like digesting entire 75,000-word books for analysis.

In overall performance, GPT-4 remains superior, but our in-house testing shows Claude 2 exceeds it in several creative writing tasks. Claude 2 also trails GPT-4 in programming and math skills based on our evaluations but excels at providing human-like, creative answers. When we prompted all the models on this list to write or rewrite a creative piece, six times out of ten, we chose Claude 2’s result for its natural-sounding human-like results. Currently, Claude 2 is available for free through the Claude AI chatbot . There’s also a $20 paid plan for access to extra features.

Despite having less financial backing than giants like OpenAI and Microsoft, Anthropic’s Claude 2 AI model holds its own against the popular GPT models and Google’s PaLM series. For an AI with fewer resources, Claude 2 is impressively competitive. If forced to bet on which existing model has the best chance of rivaling GPT in the near future, Claude 2 seems the safest wager. Though outgunned in funding, Claude 2’s advanced capabilities suggest it can go toe-to-toe with even well-funded behemoths (though it’s worth noting that Google has made several large contributions to Anthropic). The model punches above its weight class and shows promise as an emerging challenger.

3. OpenAI’s GPT-3.5

Image Credit: Marcelo Mollaretti/Shutterstock

While overshadowed by the release of GPT-4, GPT-3.5 and its 175 billion parameters should not be underestimated. Through iterative fine-tuning and upgrades focused on performance, accuracy, and safety, GPT-3.5 has come a long way from the original GPT-3 model. Although it lacks GPT -4’s multimodal capabilities and lags behind in context length and parameter count, GPT-3.5 remains highly capable, with GPT-4 being the only model able to surpass its all-around performance decisively.

Despite being a second-tier model in the GPT family, GPT-3.5 can hold its own and even outperform Google and Meta’s flagship models on several benchmarks. In side-by-side tests of mathematical and programming skills against Google’s PaLM 2, the differences were not stark, with GPT-3.5 even having a slight edge in some cases. More creative tasks like humor and narrative writing saw GPT-3.5 pull ahead decisively.

So, while GPT-4 marks a new milestone in AI, GPT-3.5 remains an impressively powerful model, able to compete with and sometimes surpass even the most advanced alternatives. Its continued refinement ensures it stays relevant even alongside flashier next-gen models.

4. Google’s PaLM 2

Image Credit: Google

When evaluating an AI model’s capabilities, the proven formula is to read the technical report and check benchmark scores, but take everything you learned with a grain of salt and test the model yourself. Counterintuitive as it may seem, benchmark results don’t always align with real-world performance for some AI models. On paper, Google’s PaLM 2 was supposed to be the GPT-4 killer, with official test results suggesting it matches GPT-4 across some benchmarks. However, in day-to-day use, a different picture emerges.

In logical reasoning, mathematics, and creativity, PaLM 2 falls short of GPT-4. It also lags behind Anthropic’s Claude in a range of creative writing tasks. However, although it fails to live up to its billing as a GPT-4 killer, Google’s PaLM 2 remains a powerful language model in its own right, with immense capabilities. Much of the negative sentiment around it stems from comparisons to models like GPT-4 rather than outright poor performance.

With 340 billion parameters, PaLM 2 stands among the world’s largest models. It particularly excels at multilingual tasks and possesses strong math and programming abilities. Although not the best at it, PaLM 2 is also quite efficient at creative tasks like writing. So, while benchmarks painted an optimistic picture that didn’t fully materialize, PaLM 2 still demonstrates impressive AI skills, even if not surpassing all competitors across the board.

5. TII’s Falcon-180B

Unless you’ve been keeping up with the rapid pace of AI language model releases, you have likely never encountered Falcon-180B. Developed by UAE’s Technology Innovation Institute, the 180 billion parameter Falcon-180 is one of the most powerful open-source language models out there, even if it lacks the name recognition of GPT models or the widespread use of Meta’s Llama 2. But make no mistake - Falcon-180B can stand toe-to-toe with the best in class.

Benchmark results reveal that Falcon-180B outperforms most open-source models and competes with commercial juggernauts like PaLM 2 and GPT-3.5. In testing math, coding, reasoning, and creative writing tasks, it even edged out GPT-3.5 and PaLM 2 at times. If ranking GPT-4, GPT-3.5, and Falcon-180B, we’d place Falcon-180B squarely between GPT-4 and GPT-3.5 for its strengths in several use cases.

While we can’t confidently say it is better than GPT-3.5 in overall performance, it makes a case for itself. While obscure, this model deserves attention for matching or exceeding the capabilities of better-known alternatives. You can try out the Falcon-180B model on Hugging Face (an open-source LLM platform).

6. Meta AI’s Llama 2

Llama 2, Meta AI’s 70 billion parameter large language model, builds on its predecessor, Llama 1. While smaller than leading models, Llama 2 significantly outperforms most publicly available open-source LLMs in benchmarks and real-world use. An exception would be the Falcon-180B.

We tested Llama 2 against GPT-4, GPT-3.5, Claude 2, and PaLM 2 to gauge its capabilities. Unsurprisingly, GPT-4 outclassed Llama 2 across nearly all parameters. However, Llama 2 held its own against GPT-3.5 and PaLM 2 in several evaluations. While it would be inaccurate to claim Llama 2 is superior to PaLM 2, Llama 2 solved many problems that stumped PaLM 2, including coding tasks. Claude 2 and GPT-3.5 edged out Llama 2 in some areas but were only decisively better in a limited number of tasks.

So, while not exceeding the capabilities of the largest proprietary models, open-source Llama 2 punches above its weight class . For an openly available model, it demonstrates impressive performance, rivaling AI giants like PaLM 2 in select evaluations. Llama 2 provides a glimpse of the future potential of open-source language models.

The Performance Gap Between AI Models Is Narrowing

Although the AI landscape is evolving at a blistering pace, OpenAI’s GPT-4 remains the leader of the pack. However, while GPT-4 remains unmatched in scale and performance, models like Claude 2 show that with enough skill, smaller models can compete in select areas. Google’s PaLM 2, despite falling short of some lofty expectations, still exhibits profound capabilities. And Falcon-180B proves that open-source initiatives can stand shoulder-to-shoulder with industry titans given sufficient resources.

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