Llama 4 Scout vs Amazon Nova Micro
Compare Llama 4 Scout and Amazon Nova Micro: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.
Updated 2026-05-21 · By Abhishek Raj · Our methodology
| Feature | Llama 4 Scout | Amazon Nova Micro |
|---|---|---|
| Category | Open Source | Compact |
| Parameters | 109B (17B active) | ~8B |
| Context Window | 512K | 128K |
| Input Price | $0.05/1M tokens | $0.001/1M tokens |
| Output Price | $0.08/1M tokens | $0.004/1M tokens |
| Latency | ~350ms | ~50ms |
Choose Llama 4 Scout when:
- ✓ Classical text analysis
- ✓ Long content
- ✓ Multi-turn
512K context, MoE efficiency, Strong multilingual
Choose Amazon Nova Micro when:
- ✓ Classification
- ✓ Intent detection
- ✓ Preprocessing
Cheapest inference, Ultra-fast, Text-only
Verdict: Llama 4 Scout vs Amazon Nova Micro
For cost efficiency, Amazon Nova Micro wins at $0.001/1M input tokens. For speed, Llama 4 Scout is faster at ~350ms. Llama 4 Scout excels at Classical text analysis while Amazon Nova Micro is better for Classification. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Llama 4 Scout costs $0.05/1M input tokens and $0.08/1M output tokens. Amazon Nova Micro costs $0.001 input and $0.004 output. Amazon Nova Micro is 50.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Llama 4 Scout has a 512K context window with ~350ms latency. Amazon Nova Micro offers 128K context at ~50ms. Llama 4 Scout has the larger context window.
Best For
Llama 4 Scout (Open Source) is optimized for: Classical text analysis, Long content, Multi-turn. Amazon Nova Micro (Compact) works best for: Classification, Intent detection, Preprocessing.
Try Both on XALEN
Both models are available through XALEN's OpenAI-compatible API. Switch between them by changing the model parameter:
from xalen import XALEN
client = XALEN(api_key="xln_test_YOUR_KEY")
# Use Llama 4 Scout
response_a = client.chat.completions.create(
model="llama-4-scout",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Amazon Nova Micro
response_b = client.chat.completions.create(
model="amazon-nova-micro",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Llama 4 Scout or Amazon Nova Micro?
Llama 4 Scout (Open Source, 109B (17B active)) offers 512K context. Amazon Nova Micro (Compact, ~8B) offers Cheapest inference. Choose Llama 4 Scout for Classical text analysis or Amazon Nova Micro for Classification.
How much does Llama 4 Scout cost vs Amazon Nova Micro?
Llama 4 Scout: $0.05/1M input, $0.08/1M output. Amazon Nova Micro: $0.001/1M input, $0.004/1M output. Both available on XALEN with batch processing at 50% discount.
Can I use both models on XALEN?
Yes. XALEN provides 200+ models through a single OpenAI-compatible API. Switch between Llama 4 Scout and Amazon Nova Micro by changing the model parameter. No code changes needed.
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Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.