Claude 3.5 Sonnet: A Deep Dive into Anthropic's Latest Model

Anthropic recently released Claude 3.5 Sonnet, and it's genuinely impressive. After spending a week putting it through its paces, here's what I've learned.

What Makes It Different

The most notable improvement is in reasoning capabilities. Claude 3.5 Sonnet handles multi-step problems with a clarity that previous models struggled with. It's not just about getting the right answer—it's about showing coherent work.

python
# Example: Claude can now handle complex code refactoring
# Before: Messy nested conditionals
def process_order(order):
    if order.status == "pending":
        if order.payment_verified:
            if order.inventory_available:
                return fulfill_order(order)
    return None

# After: Claude suggests this cleaner approach
def process_order(order):
    if not all([
        order.status == "pending",
        order.payment_verified,
        order.inventory_available
    ]):
        return None
    return fulfill_order(order)

Benchmark Performance

On standard benchmarks:

• MMLU: 88.7% (up from 86.8%)
• HumanEval: 92.0% (significant jump)
• GSM8K: 96.4% (near-ceiling)

But benchmarks only tell part of the story.

Real-World Testing

I tested it on three production tasks:

1. Code review: Caught subtle bugs that static analyzers missed
2. Technical writing: Produced documentation that actually made sense
3. Data analysis: Generated valid SQL for complex queries on first try

The Limitations

It's not perfect. I noticed:

• Occasional overconfidence on ambiguous questions
• Context window still matters for long documents
• Creative writing can feel formulaic

Verdict

Claude 3.5 Sonnet is the best general-purpose model I've used. For most tasks, it's the one I reach for first.