Generative AI is no longer just a promise of the future — it’s now a powerful tool driving real impact in business processes. Llama 4 is now available on Amazon Bedrock, and its integration with Meta’s language model marks a turning point for organisations seeking powerful AI outcomes without technical complexity.
What is Llama 4, and why is everyone talking about it?
Llama 4 is the latest generation of language models developed by Meta. It’s built on a Mixture of Experts (MoE) architecture, which allows different parts of the model to activate depending on the task, cutting computational costs without sacrificing performance. It’s also a multimodal model, meaning it can handle not only text but also images — opening the door to a wider range of use cases.
Now available via Amazon Bedrock
The big news is that Llama 4 can now be accessed through Amazon Bedrock, AWS’s serverless platform for working with foundation models from various providers (Anthropic, Mistral, Meta, Amazon, and others) — no infrastructure or training needed.
Two model variants available:
- Llama 4 Maverick 17B: A multimodal model with 400 billion parameters and a context window of 1 million tokens. Ideal for complex tasks and deep analysis.
- Llama 4 Scout 17B: A more efficient version with 109 billion parameters and a context window of up to 3.5 million tokens — expected to increase to 10M soon.
What can it bring to your business?
1. Power without technical hassle
Amazon Bedrock allows you to leverage advanced models without building your own infrastructure, making it ideal for companies wanting results without overstretching their technical teams.
2. Seamless integration with your AWS ecosystem
From S3 storage to Lambda workflows or data analysis in SageMaker, Bedrock integrates naturally with the rest of Amazon Web Services.
3. Scalability and security
Perfect for both proof of concept and full-scale deployment. Plus, it complies with enterprise-grade security standards — essential if you’re handling sensitive data.
4. Real use cases
- Personalised content generation
- Document analysis and summarisation
- Multilingual virtual support
- Automation of customer service and back-office processes
But… is it really that simple?
No — and that’s where the real value of working with a specialist team comes in.
Implementing Llama 4 through Bedrock isn’t just about calling an API. It involves:
- Designing meaningful, measurable use cases
- Fine-tuning prompts to generat