Nano Banana (Gemini 2.5 Flash Image) vs Llama 4 Scout 17B-16E Instruct
Nano Banana (Gemini 2.5 Flash Image) (2025) and Llama 4 Scout 17B-16E Instruct (2025) are compact production models from Google DeepMind and AI at Meta. Nano Banana (Gemini 2.5 Flash Image) ships a 33K-token context window, while Llama 4 Scout 17B-16E Instruct ships a 328K-token context window. On pricing, Llama 4 Scout 17B-16E Instruct costs $0.08/1M input tokens versus $0.3/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 4 Scout 17B-16E Instruct is ~275% cheaper at $0.08/1M; pay for Nano Banana (Gemini 2.5 Flash Image) only for provider fit.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-01 | 2025-04-05 |
| Context window | 33K | 328K |
| Parameters | — | 17B |
| Architecture | decoder only | mixture of experts |
| License | Unknown | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nano Banana (Gemini 2.5 Flash Image) | Llama 4 Scout 17B-16E Instruct |
|---|---|---|
| Input price | $0.3/1M tokens | $0.08/1M tokens |
| Output price | $30/1M tokens | $0.3/1M tokens |
| Providers |
Capabilities
| Capability | Nano Banana (Gemini 2.5 Flash Image) | Llama 4 Scout 17B-16E Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Llama 4 Scout 17B-16E Instruct. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Nano Banana (Gemini 2.5 Flash Image) lists $0.3/1M input and $30/1M output tokens, while Llama 4 Scout 17B-16E Instruct lists $0.08/1M input and $0.3/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Scout 17B-16E Instruct lower by about $9.06 per million blended tokens. Availability is 3 providers versus 8, so concentration risk also matters.
Choose Nano Banana (Gemini 2.5 Flash Image) when provider fit are central to the workload. Choose Llama 4 Scout 17B-16E Instruct when long-context analysis, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Nano Banana (Gemini 2.5 Flash Image) or Llama 4 Scout 17B-16E Instruct?
Llama 4 Scout 17B-16E Instruct supports 328K tokens, while Nano Banana (Gemini 2.5 Flash Image) supports 33K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Nano Banana (Gemini 2.5 Flash Image) or Llama 4 Scout 17B-16E Instruct?
Llama 4 Scout 17B-16E Instruct is cheaper on tracked token pricing. Nano Banana (Gemini 2.5 Flash Image) costs $0.3/1M input and $30/1M output tokens. Llama 4 Scout 17B-16E Instruct costs $0.08/1M input and $0.3/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Nano Banana (Gemini 2.5 Flash Image) or Llama 4 Scout 17B-16E Instruct open source?
Nano Banana (Gemini 2.5 Flash Image) is listed under Unknown. Llama 4 Scout 17B-16E Instruct is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, Nano Banana (Gemini 2.5 Flash Image) or Llama 4 Scout 17B-16E Instruct?
Llama 4 Scout 17B-16E Instruct has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Nano Banana (Gemini 2.5 Flash Image) and Llama 4 Scout 17B-16E Instruct?
Nano Banana (Gemini 2.5 Flash Image) is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Llama 4 Scout 17B-16E Instruct is available on OpenRouter, Together AI, Fireworks AI, DeepInfra, and GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Nano Banana (Gemini 2.5 Flash Image) over Llama 4 Scout 17B-16E Instruct?
Llama 4 Scout 17B-16E Instruct is ~275% cheaper at $0.08/1M; pay for Nano Banana (Gemini 2.5 Flash Image) only for provider fit. If your workload also depends on provider fit, start with Nano Banana (Gemini 2.5 Flash Image); if it depends on long-context analysis, run the same evaluation with Llama 4 Scout 17B-16E Instruct.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.