GPT-4 Turbo vs Claude 2.1: Next-Gen AI Models

Artificial intelligence (AI) has been advancing at an incredible pace recently. Two models leading this charge are GPT-4 Turbo from OpenAI and Claude 2.1 from Anthropic. 

Both boast impressive capabilities, but they also have key differences in context window size, multimodal features, pricing, knowledge cutoff dates, performance attributes, and ideal use cases.

This epic battle between the AI heavyweights comes down to their specialized strengths. GPT-4 Turbo wins for multimodal creative applications, while Claude 2.1 dominates large text processing needs. Choosing the right one depends entirely on your needs.

Key Takeaways

• GPT-4 Turbo has multimodal capabilities to process text, images, audio, video etc., while Claude 2.1 focuses solely on text processing. This makes GPT-4 better for creative applications.
• Claude 2.1 has a much larger context window of 200k tokens compared to GPT-4 Turbo's 128k tokens. This allows Claude to deeply analyze long documents.
• GPT-4 Turbo knowledge cutoff is April 2023, giving it an edge in comprehending very recent events over Claude 2.1's early 2023 cutoff.
• GPT-4 Turbo is better at coding, while Claude 2.1 shines in copywriting and human-sounding responses.

Release Dates

The new model from OpenAI was released on November 6th at DevDay. Anthropic released their new model Claude 2.1 after OpenAI's drama that resulted in the new board and Sam Altman back at the reins.

Differences Between GPT-4 Turbo and Claude 2.1

Interface

Both GPT-4 Turbo and Claude 2.1 are available in chat interfaces (ChatGPT and Claude Chat, respectively) and as APIs. ChatGPT pro users in ChatGPT plus will get access to GPT-4 Turbo. Claude Pro users already got access to Claude 2.1.

The full power of the model is typically reserved to the API. Just like it was with the good old GPT-4, chat interfaces are typically limited in how they interact with the model. They have limited response sizes, tend to overload for larger context windows, and don’t allow users to change the temperature of the model, determining creativity.

Larger Context Windows

One major area where Claude 2.1 pulls ahead is its industry-leading 200k token context window, nearly twice the context length of GPT-4 Turbo, which allows it to process large documents up to 150,000 words or 500 pages long. Anthropic has achieved an unmatched context window length in the AI industry so far.

This massive context length for ingesting textual information allows Claude 2.1 to deeply analyze long documents like research papers, financial reports, literature works, and more.

Comparatively, GPT-4 Turbo has a 128k token context capacity. While still very large, the larger context window helps enhancing Claude's ability to reason. Claude had an edge in the previous generation too, where Claude 2.0 boasted 100k and GPT-4 was stuck at 32k.

Multimodal Capabilities

GPT-4 Turbo breaks new ground with unique strengths - the ability to process and connect text, images, audio, video, and other formats. This opens the door to highly creative applications. It can also be paired with the new Assistants API, enabling a much larger set of use cases (including voice-enabled workflows). To be precise, GPT-4 Turbo itself doesn't have multimodal capabilities, but it can be paired with the other APIs by default in ChatGPT and is easy to assign to an Assistants API to enable multimodal workflows.

Claude 2.1 focuses solely on text, lacking these multimodal features even when paired with other APIs from Anthropic. It can generate tables and follow markdown formatting, but it doesn’t have any image or audio generation features, nor does the company feature interfaces where you can combine Claude 2.1 with “plugins” (or custom GPTs”). 

GPT-4 Turbo has greater versatility for projects needing a fusion of content types, allowing users for more flexibility.

Pricing

OpenAI designed GPT-4 Turbo to be more affordable than GPT-4 at $0.01 per 1,000 tokens for input and $0.03 per 1,000 for output. That's nearly 3x cheaper than GPT-3 pricing.

However, Claude 2.1 pricing is still cheaper, at $8 per million tokens in input and $24 per million tokens in output. Given the smaller training dataset and fewer free accounts they need to support on Claude Chat, Anthropic can afford to make these cheaper for the end users.

It's worth noting end users won't likely incur the costs. For example, we include unlimited generations (with very high caps) and use GPT-4 for data exploration in Akkio with our agency-tailored Chat Explore functionality.

Knowledge Cutoff Dates

GPT-4 Turbo also boasts a more recent knowledge cutoff date of April 2023 compared to Claude 2.1's early 2023 date. Those few months make a difference in comprehending very recent current events.

Additionally, GPT-4 Turbo will likely be part of ChatGPT soon, where web browsing is enabled by default in the multimodal chat.

JSON & Functions

GPT-4 Turbo supports function calling and JSON formatting, something Claude 2.1 doesn’t concern itself with for the time being. It’s fair to say their core focus has always been expanding the context.

Alignment

Anthropic and OpenAI are fundamentally different companies, and follow separate paths to develop AI for humanity. 

OpenAI’s recent drama highlighted their complicated and atypical setup, with a small nonprofit organization managing the reins of the company. Microsoft backed OpenAI in 2023 with over $10b in investment, and OpenAI trains their models in Azure.

On the other hand, Claude is developed by Anthropic, a company that is developing a sort of “code of conduct” for AI models. Amazon will invest up to $4b in Anthropic, and they might be benefiting from the partnership with the newly released Amazon Q in AWS.

What this means is that OpenAI is deemed to evolve and ship products way faster than Anthropic, because they follow a less restrictive set of rules before pushing something out. Also, if you care about privacy, you might need to check their policy to make sure they're not training the model on your data. Akkio guarantees data privacy and security on our platform when using GPT-4.

For example, image recognition wasn’t available in the API until November 2023. During the DevDay, Sam Altman (CEO of OpenAI) announced GPT-4 Vision, a leap forward in the realm of image recognition, and GPT voices.

We’re unlikely to see anything like this from Anthropic in the near future, as both features have the potential to disrupt industries and trigger privacy concerns. Anthropic's commitment is towards AI safety.

Performance Benchmarks

Now diving into performance tests, some intriguing differences emerge between these AI capabilities too.

Recall Accuracy Over Long Contexts

Research from Anthropic shows Claude 2.1 maintaining strong accuracy even with larger context lengths.

By comparison, GPT-4 Turbo still has a lower context window to refer to.

Precision With Shorter Contexts

According to The Decoder, for shorter excerpt lengths GPT-4 Turbo actually demonstrates better precision than Claude 2. This is likely due to GPT-4 Turbo's enhanced capabilities and knowledge also indirectly boosting its text comprehension.

Hallucination Rates

While we don’t yet have testing to demonstrate the model least likely to hallucinate overall, both GPT-4 Turbo and Claude 2.1 claim to be better than their predecessors.

Claude 2.1 has shown a reduction in rates of hallucination and false claims by 50%, making it more reliable for enterprises deploying AI responsibly across customer-facing applications

GPT-4 Turbo isn’t marketed to be particularly different from GPT-4 in this regard, which scored 40% higher than GPT-3.5 on internal adversarial factuality evaluations.

Math Skills

LLM models are not good at math. This is universally true. GPT-4 was better at math and coding than Claude 2, and we can assume the same will hold true with this new models.

The strengths of Claude 2 were reasoning and contextual answers, which derived from the larger 200k token context window. The same can be said for the new Claude 2.1

Ideal Use Cases for GPT-4 Turbo

GPT-4 Turbo’s clear advantages are its multimodal features, the integration with the Assistans API, and GPT-4 Vision. Hence, these are the best fits for the model: 

• Coding: GPT-4 has been long used for Github Copilot, the leading coding assistant for developers worldwide, now available in Visual Studio as well. GPT-4 Turbo has similar capabilities at a much cheaper price point;
• Visualization: together with the Assistants API, GPT-4 Turbo can write and execute Python code in a sandboxed environment. This enables graph generation and visualizations of all kinds; 
• Data Analysis: thanks to Code Interpreter, available through the Assistants API when selecting GPT-4 turbo preview as core model, the LLM can perform data preparation to clean datasets, merge columns, and even generate quick machine learning models. While specialized solutions like Akkio are much better if this is your only use case, GPT-4 Turbo through the Assistants API is still a valuable option for developers in the field; 

GPT-4 Turbo is also likely going to be in ChatGPT too, joining OpenAI’s ecosystem of apps. ChatGPT plus users now have access to a stunningly big set of features, with DALL-E 3 for image generation, GPT-4 for text generation, coding, and code interpreter, plus image generation - all in one monthly package. If you're a data analyst or an agency providing services to your clients, a platform like Akkio can offer features in terms of data preparation, exploration, machine learning, and much more without coding.

Ideal Use Cases for Claude 2.1

Claude 2.1 is significantly better than GPT-4 Turbo for all industries where input size matters. For example: 

• Legal analysis: do you need to analyze 400 pages of long form documents? Claude 2.1 can do it in a heartbeat and return with contextual information. Accuracy is likely to be higher than with other LLMs. You will feel the difference thanks to the larger context window;
• Writing: model outputs are only as good as your input. By providing way more data to work with, Claude 2.1 is typically better at generating quality long-form content and human-sounding language; 
• Book reviews: if you need to summarize or “talk with” books, Claude 2.1’s context will be a massive assist;
• Ads: thanks to the more natural-sounding text, Claude 2.1 is great at generating marketing copy for your ads on Googl & Microsoft search or social networks like Meta and YouTube.

A Note About Custom GPTs 

OpenAI released Custom GPTs at DevDay. It’s not clear which model these use, but it’s probably going to be GPT-4 Turbo soon as it’s cheaper and faster than GPT-4 (which still performs better for some tasks, though). 

Custom GPTs enable everyone, non-coders included, to generate custom chatbots to help with all sorts of things, from laundry management to coding the next masterpiece.

Users already shipped tens of thousands of GPTs, showcasing a growing demand for personalized ai. You can try a couple of interesting ones here: Grimoire for coding generation, and SEO Wizard for SEO tips.

Custom GPTs have access to all features the Assistants API provide (and likely are simple wrappers for the API), meaning you get Code Interpreter for Python code execution, DALL-E 3 for image generation, Web Browsing, and Custom Knowledge to upload your own files included.

While Claude from Anthropic doesn’t provide anything similar in their core chat product, you can develop your own custom AIs with Claude 2.1 with external software like MindStudio by YouAi. It's similar to Custom GPTs. Of course, we suggest choosing custom software for your use case for more complex use cases, like Akkio for agencies and data analysis.

MindStudio supported Claude 2.1 a few minutes after release, and lets you build custom AIs without coding. These also support custom functions (to generate images, for example), document retrieval, and heavy prompt engineering. Additionally, MindStudio works with the Claude API to let users choose temperature, maximum response size, and even how the output is displayed.

Long story short, you can use external solutions to develop Custom Agents with Claude 2.1, but GPT-4 Turbo will always be easier to use on that end due to OpenAI’s massive reach and the scale of ChatGPT, their “marketing” product.

Conclusion

GPT-4 Turbo and Claude 2.1 both demonstrate immense capabilities, but have clear differentiation too across context capacity, modal features, pricing, knowledge timeframes, performance attributes and ideal real-world applications.

If you need AI for coding and larger knowledge base, GPT-4 Turbo is likely the best choice for you.

If extensive text comprehension and analysis are critical, Claude 2.1 is likely the superior choice.

So rather than a single winner, it comes down to matching each AI giant's specialized strengths to your needs. Their rapid evolution means both continue raising the bar for artificial intelligence, to all our benefit.

But with precision tuning to specific use cases, both these models can enhance productivity enormously thanks to incredible advances from OpenAI, Anthropic and the AI community as a whole.

The future looks bright as Claude 2.1, GPT-4 Turbo and subsequent iterations get integrated into workflows across industries and domains. Third party developers are also jumping on the new models to build cheaper and/or better features.