Anthropic announced the Claude 3 model family last month, which sets new industry benchmarks across various cognitive tasks. I am always excited to see what comes from Anthropic, so I was eager to see this group arrive.
The family includes three state-of-the-art models in ascending order of capability: Claude 3 Haiku, Claude 3 Sonnet, and Claude 3 Opus. Each successive model offers increasingly powerful performance, allowing users to select the optimal balance of intelligence, speed, and cost for their specific application.
Opus, Haiku, and Sonnet are now available in claude.ai, and the Claude API is generally available in 159 countries. All Claude 3 models show increased capabilities in analysis and forecasting, nuanced content creation, code generation, and conversing in non-English languages like Spanish, Japanese, and French.
Let’s take a look at each member of the Claude 3 family:
Opus
Opus is considered the most intelligent model. It outperforms its peers on most of the standard evaluation benchmarks for AI systems, including undergraduate-level expert knowledge (MMLU), graduate-level expert reasoning (GPQA), basic mathematics (GSM8K), and more. It exhibits near-human comprehension and fluency levels on complex tasks, leading the frontier of general intelligence. It can navigate open-ended prompts and sight-unseen scenarios with remarkable fluency and human-like understanding. Opus shows us the outer limits of what’s possible with generative AI.
Haiku
Claude 3 Haiku is the fastest, most compact model for near-instant responsiveness. With state-of-the-art vision capabilities, it caters to various enterprise applications, excelling in analyzing large volumes of documents. Its affordability, security features, and availability on platforms like Amazon Bedrock and Google Cloud Vertex AI make it transformative for developers and users alike.
Sonnet
Sonnet balances intelligence, speed, and cost, making it well-suited for various applications. Notably, it is approximately twice as fast as its predecessor, Claude 2.1. Sonnet excels in tasks requiring rapid responses, such as knowledge retrieval and sales automation. Additionally, it demonstrates a unique understanding of requests and is significantly less likely to refuse answers that push system boundaries. With sophisticated vision capabilities, including the ability to process visual formats like photos, charts, and technical diagrams, Claude 3 Sonnet represents a significant advancement in AI language models.
Let’s Talk Capabilities
Near-instant results
The Claude 3 models can power live customer chats, auto-completions, and data extraction tasks where responses must be immediate and real-time.
Haiku is the fastest and most cost-effective model in its intelligence category. It can read an information- and data-dense research paper on arXiv (~10k tokens) with charts and graphs in less than three seconds. Following its launch, Anthropic is expected to improve performance even further.
For the vast majority of workloads, Sonnet is 2x faster than Claude 2 and Claude 2.1 and has higher levels of intelligence. It excels at tasks demanding rapid responses, like knowledge retrieval or sales automation. Opus delivers similar speeds to Claude 2 and 2.1 but with much higher levels of intelligence.
Strong vision capabilities
The Claude 3 models have sophisticated vision capabilities that are on par with other leading models. They can process various visual formats, including photos, charts, graphs, and technical diagrams. Anthropic is providing this new modality to enterprise customers, some of whom have up to 50% of their knowledge bases encoded in PDFs, flowcharts, or presentation slides.
Fewer refusals
Previous Claude models often made unnecessary refusals that suggested a need for more contextual understanding. Anthropic has made substantial progress in this area: Opus, Sonnet, and Haiku are significantly less likely to refuse to answer prompts that border on the system’s guardrails than previous generations of models. The Claude 3 models show a more nuanced understanding of requests, recognize actual harm, and refuse to answer harmless prompts much less often.
Improved accuracy
Businesses of all sizes rely on models to serve their customers, making it imperative for model outputs to maintain high accuracy at scale. To assess this, Anthropic uses many complex, factual questions that target known weaknesses in current models. Anthropic categorizes the responses into correct answers, incorrect answers (or hallucinations), and admissions of uncertainty, where the model says it doesn’t know the answer instead of providing inaccurate information. Compared to Claude 2.1, Opus demonstrates a twofold improvement in accuracy (or correct answers) on these challenging open-ended questions while exhibiting reduced incorrect answers.
In addition to producing more trustworthy responses, Anthropic will soon enable citations in their Claude 3 models so they can point to precise sentences in reference material to verify their answers. This is a plus for any AI tool.
Extended context and near-perfect recall
The Claude 3 family of models initially offered a 200K context window upon launch. However, all three models can accept inputs exceeding 1 million tokens and may make this available to select customers who need enhanced processing power.
To process long context prompts effectively, models require robust recall capabilities. The ‘Needle In A Haystack’ (NIAH) evaluation measures a model’s ability to recall information from a vast corpus of data accurately. Anthropic enhanced the robustness of this benchmark by using one of 30 random needle/question pairs per prompt and testing on a diverse crowdsourced corpus of documents. Claude 3 Opus not only achieved near-perfect recall, surpassing 99% accuracy, but in some cases, it even identified the limitations of the evaluation itself by recognizing that the “needle” sentence appeared to be artificially inserted into the original text by a human.
Responsible design
Anthropologists developed the Claude 3 family of models to be as trustworthy as they are capable. They have several dedicated teams that track and mitigate various risks, ranging from misinformation and CSAM to biological misuse, election interference, and autonomous replication skills. These efforts are much appreciated in a space where misinformation is often overlooked. Anthropologists continue to develop methods such as constitutional AI that improve the safety and transparency of their models, and they have tuned their models to mitigate privacy issues that could be raised by new modalities.
Addressing biases in increasingly sophisticated models is an ongoing effort, and Anthropic has made strides with this new release. They remain committed to advancing techniques that reduce biases and promote greater neutrality in their models.
Easier to use
The Claude 3 models are better at following complex, multi-step instructions. They are particularly adept at adhering to brand voice and response guidelines and developing customer-facing experiences. This is a plus for UX developers. In addition, the Claude 3 models are better at producing popular structured output in formats like JSON, making it more straightforward to instruct Claude on use cases like natural language classification and sentiment analysis.
Claude 3
Now that you’ve been introduced to the Claude 3 model family, the next question is, where do you begin to explore? Haiku, Sonnet, Opus—there isn’t a wrong choice with Claude 3. Each is like a polished gem with different characteristics, intelligence, speed, and versatility. I envision long hours pondering documentation and building with each one of them.
I’m looking forward to the upcoming feature, citations. It’s like adding footnotes to the grand library of AI. Imagine these models pointing to precise sentences in reference material, like scholars citing ancient scrolls. Seriously, I can’t wait for this feature to come out! Claude 3 creates trust and transparency, a solid foundation for AI innovations. The Claude family is a welcome addition to this space. I looked forward to the next chapter with Anthropic.
