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Aion-RP 1.0 (8B) vs Nano Banana (Gemini 2.5 Flash Image)
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
Nano Banana (Gemini 2.5 Flash Image)
Context window
33K
32,768 tokens · ~25K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Same context window size for both models.
Aion-RP 1.0 (8B) and Nano Banana (Gemini 2.5 Flash Image) have identical context windows (32K tokens). Nano Banana (Gemini 2.5 Flash Image) is 62% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
RAG / high-volume retrieval
Use Nano Banana (Gemini 2.5 Flash Image). Input tokens are 62% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Nano Banana (Gemini 2.5 Flash Image). Its 32K max output lets you generate complete artifacts in one request.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Aion-RP 1.0 (8B) | Nano Banana (Gemini 2.5 Flash Image) |
|---|---|---|
| Context window | 32,768 tokens (32K) | 32,768 tokens (32K) |
| Max output tokens | 29,491 tokens (29K) | 32,768 tokens (32K) |
| Speed tier | Fast | Fast |
| Vision | No | Yes |
| Function calling | No | No |
| Extended thinking | No | No |
| Prompt caching | No | Yes |
| Batch API | No | No |
| Release date | Feb 2025 | Oct 2025 |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | Aion-RP 1.0 (8B) in | Aion-RP 1.0 (8B) out | Nano Banana (Gemini 2.5 Flash Image) in | Nano Banana (Gemini 2.5 Flash Image) out |
|---|---|---|---|---|
| Openrouter | $0.800/M | $1.60/M | $0.300/M | $2.50/M |
Frequently asked questions
Powered by Mem0
Use a smaller model.
Get better results.
Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model