Llama 4 offers larger context windows and broader multilingual pre-training, making it suitable for tasks requiring extensive context and multilingual support. Claude 5 excels in reasoning and coding with a focus on safety, making it ideal for applications demanding high accuracy and ethical considerations. The choice depends on specific needs: Llama 4 for large-scale data processing and multilingual applications, and Claude 5 for reasoning-intensive and safety-critical tasks.
| Attribute | Claude 5 | Llama 4 |
|---|---|---|
| Context Window Size | 200,000 tokens (approximately 150,000 words or over 500 pages). Some use cases expanding to 1 million tokens. | Llama 4 Scout: 10 million tokens, Llama 4 Maverick: 1 million tokens |
| Maximum Token Output | The context window covers both input and output tokens. | Not specified in search results |
| Training Data Size | Not available | Over 30 trillion tokens, including diverse text, image, and video data |
| Finetuning Capabilities | Can be fine-tuned using high-quality prompt-completion pairs. Fine-tuning Claude 3 Haiku is generally available in Amazon Bedrock. | Enables open-source fine-tuning, pre-trained on 200 languages, uses techniques like LoRA for efficient fine-tuning |
| Multilingual Support | Robust multilingual capabilities with strong performance in zero-shot tasks across languages. Claude 3.5 supports over 30 languages and maintains consistent relative performance across both widely-spoken and lower-resource languages. | Pre-trained on 200 languages, with over 100 having more than 1 billion tokens each. Supports 12 languages including Arabic, English, French, German, Hindi, Indonesian, Italian, Portuguese, Spanish, Tagalog, Thai, and Vietnamese. Image understanding is primarily in English. |
| Coding Proficiency | Proficient in coding. Claude 3.5 Sonnet can independently write, edit, and execute code with sophisticated reasoning and troubleshooting capabilities. | Understands and generates application code, but coding performance can be inconsistent, struggling with complex or domain-specific problems |
| Reasoning Ability | Strong reasoning abilities. Claude 3.5 Sonnet sets new industry benchmarks for graduate-level reasoning. Claude Opus 4 excels at advanced coding and delivers sustained performance on long-running tasks. | Enhanced reasoning through supervised fine-tuning and online reinforcement learning. Llama 4 Maverick was co-distilled from Llama 4 Behemoth to improve performance on math and reasoning tasks. |
| Hallucination Rate | Designed to reduce hallucinations, but they can still occur. Claude has a relatively low hallucination rate. Internal evaluations have shown that Claude Opus 4 had a higher hallucination rate than Claude 3.7. An ideal hallucination rate for AI-driven sales tools should be less than 5%. | Andri.ai reduces hallucinations through direct mapping of questions to verified citations. |
| Bias and Safety Measures | Built with principles that prioritize user welfare and fairness, incorporating features designed to minimize bias and prevent the generation of harmful content. Uses Constitutional AI, based on a written set of ethical principles. | Includes AI safety mechanisms in the model pipeline, uses data filtering and other mitigations during pre-training, employs techniques to ensure models conform to helpful and safe policies during post-training, uses tools like Llama Guard, Prompt Guard, and CyberSecEval, aims to provide unbiased answers and respond to different viewpoints without judgment |
| API Availability and Cost | Available through the Anthropic API, Amazon Bedrock, and Google Cloud's Vertex AI. Claude 3.5 Sonnet costs $3 per million input tokens and $15 per million output tokens, with a 200K token context window. | API costs range from $0.10 to $0.90 per million tokens. Llama 4 Scout: $0.15 input/$0.50 output per 1 million tokens. Cerebras: $0.65 per million input tokens and $0.85 per million output tokens. Llama 4 Maverick: $0.22 input/$0.85 output per 1 million tokens. Meta quotes a blended cost assuming 3 input: 1 output tokens. |
| Speed of Response | Claude 3.5 Sonnet operates at twice the speed of Claude 3 Opus. | Llama 4 Scout runs at 2,600 tokens per second on Cerebras. Built for speed and has fast response times and low latency. |
| Availability of Open Source Weights | Not available | Meta refers to its Llama 4 models as open source, though the community license is not an official Open Source Initiative-approved license. Models are freely available for download and use by researchers and developers, but services exceeding 700 million monthly active users require a separate license. |