Nano Banana 2 Lite vs Llama 4
Pricing, benchmarks, and use case comparison
Quick take
- •Llama 4 is meaningfully stronger at long context (95 vs 0).
Specs comparison
| Nano Banana 2 Lite | Llama 4 | |
|---|---|---|
| Provider | Meta | |
| Type | Closed source | Open source |
| Context window | Not announced | ✓Up to 10M tokens (Scout); ~1M tokens (Maverick) |
| Input / 1M tokens | Not announced | Free (self-host) |
| Output / 1M tokens | 33.6 | Free (self-host) |
| Release date | 2026-06 | 2025-04 |
Benchmarks
| Benchmark | Nano Banana 2 Lite | Llama 4 |
|---|---|---|
| Arena.ai Text-to-Image Leaderboard | Ranked #5 | - |
| Text-to-Image Elo Score | 1251 | - |
| Single-Image Editing Elo Score | 1308 | - |
| Multiple-Image Editing Elo Score | 1294 | - |
| 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 Nano Banana 2 Lite if...
- →When cost-per-sample is the primary constraint
- →For workflows requiring 100+ images per session
- →When generation latency must be under 5 seconds
- →For rapid prototyping and exploration
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