Llama 4 Scout vs Nano Banana (Gemini 2.5 Flash Image)
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Llama 4 Scout and Nano Banana (Gemini 2.5 Flash Image).
Llama 4 Scout
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
Nano Banana (Gemini 2.5 Flash Image)
Gemini 2.5 Flash Image, a.k.a. "Nano Banana," is now generally available. It is a state of the art image generation model with contextual understanding. It is capable of image generation,...
Technical Specifications
| Specification | Llama 4 Scout | Nano Banana (Gemini 2.5 Flash Image) |
|---|---|---|
| Provider | Meta | |
| Context Window | 10,000,000 tokens | 32,768 tokens |
| Agent Suitability | 82/100 | N/A |
| Time to First Token (TTFT) | 350 ms | N/A |
| Deployment Model | self hostable | managed api |
| Production Stability | beta | stable |
| API Available | Yes | Yes |
| Released Date | 2025-04-05 | 2025-10-07 |
API Pricing Comparison
Input Price per Million Tokens
Llama 4 Scout
$0.10
Nano Banana (Gemini 2.5 Flash Image)
$0.30
Output Price per Million Tokens
Llama 4 Scout
$0.30
Nano Banana (Gemini 2.5 Flash Image)
$2.50
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Llama 4 Scout Quirks & Gotchas
- ▸10M context causes significant VRAM pressure — recommend 4-bit quantization
- ▸Primarily designed for RAG, not agentic tool calling
Nano Banana (Gemini 2.5 Flash Image) Quirks & Gotchas
No developer gotchas reported.