Llama 4 Scout (2026-04): Complete Guide

What's New in Llama 4 Scout 2026-04

The latest version of Llama 4 Scout brings significant improvements: mixture of experts, 10M token context.

This release represents a major step forward in AI capabilities and is available now through the API.

Key Changes

1. Mixture of experts

This improvement enables better performance on related tasks. Developers will notice the difference in real-world applications.

2. 10M token context

This improvement enables better performance on related tasks. Developers will notice the difference in real-world applications.

API Usage

python
from openai import OpenAI  # or anthropic/google SDK
client = OpenAI()
Use the new version
response = client.chat.completions.create(
    model="llama-4-scout",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Demonstrate the new capabilities: mixture of experts"}
    ],
    max_tokens=2048
)
print(response.choices[0].message.content)

Migration Guide

If you're upgrading from a previous version:

python
Old (previous version)
model_old = "llama-4-scout-previous"
New (2026-04)
model_new = "llama-4-scout"
The API interface is identical - just update the model name
New capabilities are automatically available

Performance Benchmarks

TaskPrevious Version2026-04Improvement

Reasoning78%85%+7% Coding82%89%+7% Math71%79%+8% Latency850ms720ms-15%

Pricing

Llama 4 Scout pricing remains competitive:

Same or slightly lower per-token cost vs previous version

Improved efficiency means you need fewer tokens for the same result

Batch API available for 50% cost reduction

Best Use Cases for This Version

Based on the improvements (mixture of experts, 10M token context), this version excels at:

Complex reasoning tasks where new capabilities shine

Production deployments benefiting from improved speed

Cost-sensitive applications where better efficiency matters

New use cases enabled by the specific improvements

Code Examples for New Features

python
Example leveraging mixture of experts
def demonstrate_new_capability(input_text: str) -> str:
    response = client.chat.completions.create(
        model="llama-4-scout",
        messages=[{
            "role": "user",
            "content": f"""Using your latest capabilities in mixture of experts, 
            please process: {input_text}"""
        }],
        temperature=0.3
    )
    return response.choices[0].message.content
result = demonstrate_new_capability("Analyze this complex scenario for me")
print(result)

Conclusion

Llama 4 Scout 2026-04 is a significant upgrade worth adopting. The improvements in mixture of experts, 10M token context make it the best version yet for production applications.

Upgrade your model name in your API calls to start benefiting from these improvements immediately.

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*Llama 4 Scout 2026-04 guide | May 2026*