Amazon Nova Pro vs Llama 4
Pricing, benchmarks, and use case comparison
Quick take
- •Llama 4 is meaningfully stronger at long context (95 vs 80).
- •Llama 4 is open-weights (free to self-host); Amazon Nova Pro is paid API only.
- •Llama 4 has a Up to 10M tokens (Scout); ~1M tokens (Maverick) context window vs 300K tokens - better for whole-repo or long-document work.
Specs comparison
| Amazon Nova Pro | Llama 4 | |
|---|---|---|
| Provider | Amazon Web Services | Meta |
| Type | Closed source | Open source |
| Context window | 300K tokens | ✓Up to 10M tokens (Scout); ~1M tokens (Maverick) |
| Input / 1M tokens | $0.80 | ✓Free (self-host) |
| Output / 1M tokens | $3.20 | Free (self-host) |
| Release date | 2024-12 | 2025-04 |
Benchmarks
| Benchmark | Amazon Nova Pro | Llama 4 |
|---|---|---|
| MMLU | ~85% | - |
| Scout context window | - | 10M tokens |
| Scout size | - | 17B active / 109B total (16 experts) |
| Maverick size | - | 17B active / 400B total (128 experts) |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose Amazon Nova Pro if...
- →You are building on AWS and want native Bedrock integration
- →You need multimodal understanding of images or video plus text
- →You want a cost-balanced general model with a large context
- →You need enterprise controls: data residency, service tiers, prompt caching
Choose Llama 4 if...
- →You need extremely long context in an open model (Scout's 10M window)
- →Self-hosted or on-prem multimodal deployment
- →You want an efficient MoE that activates few parameters per token
- →Fine-tuning or full control over the model